Shortcomings of Animal Models and the Rise of Engineered Human

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The shortcomings of animal models and the rise of engineered human cardiac tissue Barry Fine, and Gordana Vunjak-Novakovic ACS Biomater. Sci. Eng., Just Accepted Manuscript • DOI: 10.1021/acsbiomaterials.6b00662 • Publication Date (Web): 19 Jan 2017 Downloaded from http://pubs.acs.org on January 21, 2017

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ACS Biomaterials Science & Engineering

The shortcomings of animal models and the rise of engineered human cardiac tissue

Barry Fine1,2 and Gordana Vunjak-Novakovic1,2 1

Department of Biomedical Engineering and 2 Department of Medicine

Columbia University

Corresponding Author: Gordana Vunjak-Novakovic, VC12-234, 622 West 168th Street, New York, NY 10032, [email protected]

Key Words: animal model, drug development, inducible pluripotent stem cell, tissue engineering,

Abstract We provide here a historical context of how studies utilizing engineered human cardiac muscle can complement and in some cases substitute animal and cell models for studies of disease and drug testing. We give an overview of the development of animal models and discuss the ability of novel human tissue models to overcome limited predictive power of cell culture and animal models in studies of drug efficacy and safety. The in vitro generation of cardiac tissue is discussed in the context of state of the art in the field. Finally we describe the assembly of multitissue platforms for more accurate representation of integrated human cardiac physiology and consider the advantages of in silico drug trials to augment our ability to predict drug-drug and organ-organ interactions in humans.

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Introduction Animals have been studied since ancient Greece in order to better understand human physiology and biology. Aristotle espoused the use of animals as early as the 6th century BC and studied embryology using chicks1. The study of human biology has been significantly propelled over millennia by the use of animal models. With the development of evolutionary principles, the notion of homology and model organisms has hastened the foray into comparative biology2. The mouse has served as a particularly highly utilized species, due in large part to its small size, short generation times, available inbreeding, large number of offspring, and the ability to reliably alter its genome3.

This model has served as an invaluable tool in studies ranging from

development to mechanisms of disease. However, in successfully predicting the effects of various therapeutic modalities in humans, the mouse has been an enormous disappointment. There are a number of reasons for such an outcome, and many laboratories are trying to build better and more rigorous approaches to testing human therapies in mice. Billions are being spent each year on therapeutic modeling in mouse, only to have nearly 90% of the candidate therapies fail in human trials, and generate massive downstream costs that further increase from year to year4-5. The existing system for preclinical studies is unsustainable because of its limited ability to recapitulate human physiology and the financial burden placed on drug development that spills over to healthcare. In this context, the pursuit of human based systems using tissue engineering and stem cell approaches has begun in earnest and, with some early optimism, may help make therapeutic selection more relevant to human disease.

The Premise of Animal Models One of the foremost difficulties in studying human physiology is in our inability to directly observe and manipulate the fundamental units of the human body. So we have turned to

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various model systems to better understand such intricacies and to make translational extrapolations back to human biology and therapeutics. Historically, this has spanned the gamut from studying fruit flies and worms, to cancer cells in a cell culture plate and complex computer models of systemic biological interactions. The study of the heart has taken many forms, from extrapolating the action potentials of Hodgkin’s and Huxley’s study of the squid axon6 to Cyon’s isolated perfusion of the frog heart7 and Langendorff’s perfusion of the mammalian heart in the 19th century8. Without the animal models, the entire field of translational medicine and many of the current medical advances would probably not exist. Animal models can come in many forms and sometimes their differences from humans are scientifically advantageous. Take the example of zebrafish. This invertebrate animal has been an invaluable tool for elucidating stages and molecular signals involved in cardiac development because of a simple difference in its embryo physiology compared to avian and mammalian counterparts – its small size9. Defects in cardiovascular development in larger animals can be associated with early embryonic lethality as the developing embryo relies heavily on oxygen delivery by that nascent vascular system. The zebrafish embryo however is so small that oxygen diffusion from surrounding fluid is sufficient to permit early embryogenesis. The result is that it can develop and survive without a cardiovascular system, enabling scientists to study deleterious defects and mutations in the cardiovascular system without compromising the entire embryo.

Furthermore, its translucency enables direct visualization of the developing

cardiovascular system. And though it may appear to be a wholly different organism compared to a human patient, its vertebrate lineage allows us to make very important connections to human physiology, especially in congenital heart disease. Zebrafish models of severe laterality disease like heterotaxy were instrumental in elucidating the Nodal pathway in these patients10. Similarly, mutations in GATA4 in patients with atrioventricular septal malformations were shown to play a causative role in the development of the septum in zebrafish11.

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The current use of animals to study human physiology is rooted in the concept of modeling by analogy, that has been originally proposed by Kant12. Analogy involves mapping or point-bypoint processing of two similar structures or objects. As biologists have been constrained by representational models more than other natural sciences, the notion of analogy has merged with the rise of evolution to generate the concept of homology. The common ancestor of related organisms is thought to tie together not only the structure of a biological system, but also its functional correlate13. This notion is based on the premise that our ability to translate findings from one organism to another is a direct function of similarity in DNA sequences. From within this principle arises the core belief among scientists that to elucidate a homologous organism is to elucidate the human body.

The Mouse Model The research in animal models has become a mainstay of biological research to the point that it accounts for approximately 50% of the NIH budget14. Koch’s postulate that established a causative relationship between a microbe and a disease was famously first demonstrated in the late 1800s in the mouse model, marking one of the true beginnings of murine experimentation carried out to predict human physiological outcomes15. Since then, the mouse has risen to the most commonly used animal for modeling human disease. The reasons for such a broad use of the mouse model are many-fold. Inbreeding has generated essentially an unlimited supply of genetically identical mice, allowing tight control over the relationship between genotypes and phenotypes, an extraordinarily important ability when manipulating the mouse genome. The mouse is small, easily transported, has fast generational times, and can be bred quickly with large litters. Genetically, the mouse has been proven to be the easiest mammal to manipulate, enabling recapitulation and mechanistic studies of disease. Because of these characteristics,

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the mouse has been an incredibly invaluable tool at many levels in studies of development, physiology, genetics and disease. Preclinical mouse models span an extensive gamut of manipulation. Cell line xenograft models in athymic nude mice have evolved into Patient Derived Xenografts (PDX), where the individual patient’s tumor cells are grown in a mouse, with the goal to tailor the therapeutic regimens by directly measuring responsiveness to different drugs and treatments16. Large-scale screens using libraries of PDX mice to recapitulate the heterogeneity of cancer hold promise for validating the known and identifying new therapeutic targets and predicting the efficacy of drugs. The mouse has been a powerful tool for probing the underpinning of cardiac development and structure using gene manipulation.

Conditional knockout of genes using Cre Lox systems

driven by cardiac specific promoters has been invaluable for studying the consequence of deleterious genetic alterations past fetal development.

This has allowed investigators to

circumvent embryonic lethality and isolate the contribution of specific genes to cardiac development and function. For instance, homozygous loss of the Isl1 transcription factor leads to aberration of ventricular looping, loss of second heart field structures and single ventricle physiology17. Similarly, heart specific deletion of the transcription factor Gata4 led to dilated heart failure with an inability to compensate with pressure overload or exercise stimulation as well as increased levels of cardiomyocyte apoptosis18. The ability to focus genetic lesions to a specific organ has been an incredible advantage of the mouse in bridging the connection between genes and their functional outputs in physiological systems. The mouse has also been invaluable in proof of concept therapies that involve genetic modulation. The mdx mouse, harboring a spontaneous mutation in the Dystrophin DMD gene is one such example. Discovered in the 1980’s, this mouse has many similar phenotypes to the human version of muscular dystrophy and was instrumental at making key discoveries underlying the disease premise and mechanism19-20. Utilization of gene editing in this disease was demonstrated when investigators used CRISPR Cas9 to correct the mutation by zygote

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injection21. The resulting mosaics had rescue of their muscle disease that was proportional to the to the level of correction in each animal, with animals at 100% correction showing essentially wild type features. This is a powerful demonstration of the mouse as a model of genetic disease and novel therapies. The substitution of the mouse immune system with a human immune system, either genetically or by functional reconstitution in immune deficient mice, has been a significant advance for studying the interplay between the tumors and the immune system22. The “humanized mouse” has been a critical advance for the field of immunomodulatory therapies which have now showed incredible efficacy in a wide range of tumors and models of transplantation. Furthermore, classic germline and conditional manipulation of the mouse genome have pioneered many of the current advances in our understanding of development, physiology and oncogenesis, with direct translational impact on cardiac diseases. For instance, the delineation of oncogenes has revealed novel pathways in cardiac hypertrophy such as c-MYC23. The study of cancer metabolism has elucidated mechanisms of ischemia, reactive oxygen species generation and mitochondrial dysfunction which all impact cardiac biology.

The field of

angiogenesis which was born out of tumor studies is now being applied to reperfusion strategies after myocardial infarction24. Likewise studies of aberrant signal transduction pathways leading to cancer (e.g. mTOR) have given us novel ways to inhibit the immune system to allow for improved transplantation outcomes25. The only problem is that for all of the advances forged in making mice with cancer, the success rate for applying those models to generate new therapy has been the lowest compared to any other field of medicine. Only one in fifteen oncology drugs taken to phase I trials actually makes it to FDA approval5. According to Richard Klausner: “The history of cancer research has been a history of curing cancer in the mouse. We have cured mice of cancer for decades and it simply didn’t work in humans.”

This sobering statement crystalizes what many in the field now

recognize as a massive shortcoming of the animal model: the prediction problem26-28.

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The Prediction Problem Historically, the Nuremberg Code is a set of ethical guidelines that guide the research ethics in human experimentation29. Within that code is the mandate to base human experiments on prior knowledge such as data from animal experimentation. From this mandate grew an immense pre-clinical industry of testing hypotheses on animals. US laws require animal testing prior to approval of a drug or device. The rise of the genetically plastic mouse has paralleled the expansion of pharmaceutical industry. But from the mouse or zebrafish to the human, there is an enormous leap. In order to appreciate the hurdles faced in trying to bring a therapy to the market, it is important to understand the human randomized controlled trial, the therapy’s clinical proving ground to establish both the safety of the drug and its efficacy in a disease state. Let us take the example of cardiovascular clinical trials, which admittedly are some of the largest due to the low event rates. The antiplatelet agent clopidogrel targets the P2Y12 receptor and inhibits ADP depdendent platelet reactivity. As platelet reactivity leads to thrombus formation in coronary arteries and thereby to myocardial infarction, clopidogrel should reduce or prevent myocardial infarctions and its sequelae30. On the other hand, inhibiting platelet function may lead to bleeding that would have otherwise been halted if the platelets had been normal. In the CURE trial, 12,562 patients with a non-ST segment elevation myocardial infarction were randomized to either receive clopidogrel and aspirin or aspirin alone for 3-12 months from the time of myocardial infarction31. On the basis of this trial’s results, clopidogrel was approved by the FDA for use during and after a myocardial infarction. Some of the most successful The primary outcome of the CURE trial was a composite of hard clinical endpoints including death from cardiovascular causes, non-fatal MI, or stroke. Over an average period of 9 months of continuous drug exposure, the primary outcome occurred in 582 out of 6259 in the clopidogrel group and 719 in the aspirin alone, generating around a 2% difference in event rate. To extrapolate that difference, an average of 50 patients (up to 100

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with the upper limit confidence interval) would need to take clopidogrel and aspirin to prevent a clinically meaningful event.

Furthermore, from the safety data that were based on the

occurrence of major bleeding, the number of patients needed to show evidence of harm (i.e. have a major bleed on clopidogrel) was around 100 as well. This seemingly narrow therapeutic balance may appear small and there was no actual mortality difference (though the study was not powered for such an outcome). However, clopidogrel was one of the most successful drugs in pharmaceutical history generating 9-10 billion dollars a year in revenue32. It is still one of the most widely prescribed cardiovascular medications today, and has likely had a massive global impact on the outcomes of myocardial infarctions. How then could an animal model ever predict a blockbuster drug that would decrease a composite endpoint clinical event in 1 out of 50 humans who had a heart attack over the course of a year? Though a 2% difference in clinical event rate may seem small, when applied to millions of humans, it can have a huge clinical impact. The prediction problem is the inability of our animal models, and in particular rodents, to predict the success of an intervention in humans. There are two components to every clinical trial that an animal study can inform upon – safety and efficacy. Unfortunately, the results have been lacking for both. In terms of safety, the rodent is able to predict toxicity in only about 43% of cases33. Because of such low predictability, the FDA has mandated that drugs be tested on a second animal more phylogenetically closer to humans such as a non-human primate. However even this two-tiered animal test is still only able to predict toxicity in only 71% of cases. The reasons of this are complex and likely involve both the genetic and environmental factors. A classic example of this failure was the Phase I clinical testing of TGN1412 in 200634.

A

humanized anti-CD28 receptor antibody developed for B cell chronic lymphocytic leukemia and rheumatoid arthritis, the drug had been extensively tested in rabbits and primates. In what has become a well known tragic set of events, initial testing of 6 human subjects at a dose of 0.2% the animal dose in humans resulted in profound vasodilatory shock from cytokine storm within

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15 minutes of the first dose, resulting in multi-organ failure and extensive morbidity in all subjects. One of the theories proposed for this discrepancy in toxicity is that the cytokine storm was due to activation of memory T cells in human subjects. Animals also have memory T cells, but those raised in sterile animal facilities have far fewer – an example of how we can fail to capture complex environmental interactions with our physiological response to medications. Prediction of efficacy, though less dramatic in its failure, has been even more rare and more disappointing with approximately 90% of therapies shown to be efficacious in animals and ultimately failing in humans12. These failures take an enormous toll. Clinical trials to prove efficacy of single drug can cost hundreds of millions of dollars and patients who enter clinical trials often have no other recourse, leaving a human and monetary toll on the healthcare system. Very few animal models can accurately recapitulate all aspects of human disease. Take for instance cystic fibrosis, a disease caused by a mutation in the chloride channel CFTR, resulting in eventual respiratory failure due to thickened bronchial secretions. Mice with the exact same human mutation exhibit no pulmonary disease and instead die of intestinal obstruction35. And even when the mouse does mimic some of the human disease symptomatology, there is no evidence that this portends any better ability to predict an outcome.

Amyotrophic lateral

sclerosis (ALS) has been successfully genetically engineered in mice using patient based mutations in superoxide dismutase, which are found in about 10% of ALS. Over the past 10 years, 12 therapies shown to work in mice were taken to the human clinical testing. All but one failed in clinical testing and the one that succeeded showed minimal benefit36.

Equally

concerning should be the number of potentially false negatives generated in animal studies. If the negative predictive value of these studies is as poor as the positive predictive value, then we might have lost innumerable therapies that may have changed the face of our clinical practice. There have been many analyses and opinions as to why animal and in particular mouse studies are such poor paradigms for human disease. The obvious physiological differences in organ

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anatomy, natural history of disease and metabolism of drugs (Figure 1) are leading to different thresholds for efficacy and toxicity between organisms, a difference that may tip the balance of whether a therapy has overall therapeutic value. There are also truly significant differences in gene expression between the mouse and human. We now know that copy number of thousands of genes differ among humans themselves and between humans and mice37-39. Also, though highly conserved at the exon level, humans and mice are only about 50% similar at the intron level40-41. Our burgeoning understanding of the importance of non-coding RNA control of expression through chromatin remodeling and transcriptional modulation is just starting to evolve. Intronic differences may prove to be quite significant when it comes to gene expression interaction with disease states. Conservation of alternate exon splicing is only approximately 20% conserved between mouse and human42. Comparative analysis of human and mouse miRNA expression showed highly significant tissue specific differences between the two43. As an example, expression analysis of fat in mouse and humans revealed that nearly a third of miRNA expressed in humans were not found in mouse while over 50% of miRNA expressed in mouse were not found in human, demonstrating a very large discordance in miRNA gene regulation44.

This gene regulation divergence likely

generates large downstream differences in physiological significant and clinically relevant states. This was remarkably demonstrated by Seok and colleagues in 2013 in an article that compared the gene expression patterns of mice and humans in response to three severe inflammatory disorders: trauma, sepsis and burns. There was essentially no correlation (R2 between 0.0 and 0.1) between human and mouse genomic response to any of the inflammatory conditions45. Based on extensive murine models of the inflammatory reaction, 150 clinical trials were conducted to test candidate agents that have blocked the inflammatory cascade in mice4648

, and not a single one of these inhibitors worked in humans.

Something that is potentially overlooked in trying to understand the limited prediction power of the mouse models may be linked to the one characteristic that has made the mouse model so

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easy to work with: inbreeding. As tools for understanding development, physiology, signaling pathways, target identification and gene characterization, genetically identical animals have been indispensable. But if a therapy is ultimately judged by its effect on a genetically very heterogeneous human population, it is conceivable that the inbred mouse may fail in predicting efficacy or safety because it presumes a single genomic – therapy interaction. The mouse does not model genetic variation and its interaction with therapeutic response, as it is essentially a test on a single individual. And as we see from clinical trials, not everyone responds to the same therapy the same way.

The simplicity of in vitro models. Returning to one of the very first steps in drug discovery, in vitro tissue culture models are based on the premise of simplification. In vitro assays compromise physiological fidelity for facility but are an incredibly important tool in terms of isolating a component or an individual output from an organ or organ system.

In terms of drug testing, this narrows to focus to

measuring outputs that scientists correlate roughly to either efficacy or toxicity but are actually manifestations of neither. Many aspects of single cell biology do not require the reconstitution of mutli-tissue systems and cell culture has been invaluable in studying cellular architecture, molecular structures, protein interactions and signal transduction pathways in isolation and in a highly controlled and easily manipulatable environment.

They have been fantastic tools at

understanding the mechanism of actions and targets of drugs, helping to predict and explain certain on and off target effects of drugs. But in vitro systems are very susceptible to artifacts and misleading results due to the lack of physiological validation and as such can be coerced easily into producing conflicting sets of data that are dependent often on unknown variables and subtle differences in technical approach. In vitro models have utilized different sources over the last century, ranging from organ explants originally described in 1897 by Loeb to precision cut tissue slices to dissociated cell cultures49.

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Dissociated cells have been widely used due to their ease of culture, low cost, quick expansion and easily manipulated gene or protein expression. They are classically grown in 2D cultures generally on a polystyrene substrate and were either derived directly from a tissue source (primary cell culture) or were immortalized from a primary cell line. The plethora and expansive nature of commercially products geared towards in vitro cell culture has quickly facilitated very detailed quantitation innumerable aspects of cellular biology. Primary cells derived directly from tissues have been difficult to handle and are time intensive. Though they should mirror the biology of the tissue from which they were derived closely, primary cells can be difficult to expand and grow, show varying levels of differentiation, and are often contaminated by supporting stromal cells. Hence immortalized cells lines have become a choice of convenience as they are more homogenous, easier to expand and are simpler to maintain. Oncogenic transformation used to generate an immortalized cell line and high passage numbers select for clonal expansion of senescent resistant cells whose altered genotypes render it phenotypically unlike its tissue of origin. Multiple studies have demonstrated significant alterations in multiple key components of the cell, including metabolic potential50, cytoskeletal organization51, extracellular receptor expression and response to inflammatory cytokines52. Thus, extrapolation of much of the data garnered from experiments with these cells is quite limited. The one exception here is the study of cancer as immortalized cell lines derived from tumors have been extensively utilized to elucidate cancer subtype specific biology. However, even in these systems, there are significant differences between physiology and cell culture. A comparison of multiple cancer cell lines with their tissue of origin demonstrated that 30% difference in overall gene expression53. Many genes that promote growth are upregulated in cell culture which may explain why cells in culture proliferate at supraphysiological levels compared to cells inside the body. Interestingly, when placed back into either an animal or grown with extracellular matrix, gene expression normalizes and proliferation returns to

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physiological levels54 demonstrating that this is a dynamic process and one that can be modeled to better represent human tissue. One of the factors underlying this loss of fidelity is the lack of the right microenvironment. The vast majority of dissociated cell culture occurs in two dimensional monolayers.

Cells on

polystyrene surfaces are exposed to similar amounts of nutrients and growth factors from a medium that does not resemble true nutrient availability in the human body.

Cells that

proliferate remain attached and cells that die detach and are removed with media changes. Cells are generally flatter than their in vivo morphology and furthermore, immortalization generally causes aberrant intracellular cytoskeletal architecture. There is a near complete lack of cell-matrix interaction and cell-cell interactions do not mimic physiological communication. Polystyrene lacks the proper extracellular signaling cues, supportive stromal cells and mechanical/elasticity profile of a native microenvironment.

Three Dimensions Assessing the efficacy and toxicity of a drug in two-dimensional culture are patently deficient and it is unclear how relevant those outputs are for predicting actual clinical events. Recently, a shift towards three dimensional cell culture has tried to bridge the deficiencies of two dimensional culture systems. 3D culture systems involve a variety of scaffold materials that span both native and synthetic polymers with diverse mechanical properties. Cell aggregates or spheroids can be generated either without a scaffold (e.g. hanging drop method or forced floating method) on a polymerized matrix or within a liquid matrix that then undergoes polymerization

The ability to embed extracellular matrix protein and specific adhesion

molecules can promote receptor-ligand responses, cell-cell interaction and natural cell morphology55-58. Heterogeneity in cell survival and proliferation correlates to nutrient diffusion and mimics closely zones of proliferating cells, quiescent cells and dying cells found in vascularized tissues59-61. Numerous studies have detailed significant gene expression changes

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in three dimensional culture systems that more closely resemble that of the native tissue compared to 2D culture62-63. Overall, cellular responses in 3D culture have been shown to be more reflective of in vivo cellular physiological responses64-68 and because of this, 3D cell culture has the potential to re-establish the potential of in vitro drug testing. This has been especially demonstrated in cancer research where a disconnect between chemosensitivity in 2D (increased sensitivity) and actual human tumors (decreased sensitivity) had been recognized for many years and was extraordinarily costly to pharmaceutical development. Recent work in 3D tumor models have shown reduced efficacy of many established and investigational antineoplastic agents compared to 2D cell cultures, including ovarian, lung, osteosarcoma, and head and neck tumors, resembling responses that are more in line with clinical trial results69-72.

iPS Cells and Inherited Diseases. Advances in stem cell differentiation and genetic manipulation have opened the door to exploring human tissue specific gene-phenotype interactions in disease modeling. iPS cells have circumvented many of the regulatory and ethical constraints of human embryonic stem cells. As differentiation protocols are advanced, the number of different cell types that can be generated has expanded greatly. iPS cells can be readily generated from patients with a disease allowing us to capture genetic variants and actually attempt human based forward genetics. In parallel, CRISPR-Cas9 and other genome editing tools have greatly accelerated the ability to make pinpoint modification in genomes, allowing facile and efficient genome wide modifications73. While mouse manipulations took months to generate and validate, it now takes just weeks to modify the genome of the iPS cells. Furthermore, advances in differentiation protocols have vastly widened the capacity of iPS cells to generate different tissues. Some of the most extensively studied human diseases are the inherited disorders of the cardiovascular system74. These studies have grown out of both the derivation of iPS lines from human patients with inherited cardiomyopathies as well as the generation of inherited mutations

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linked to cardiomyopathies using facile gene editing strategies75. iPS cells have also played a role in studies of acquired disorders following exposures to certain toxic agents. Channelopathies Given the strong genetic underpinning of many inherited disorders of the heart, human iPS cells have been used to model a number of clinically relevant channelopathies. Long QT syndrome (LQTS), characterized as a propensity for Torsades de Pointes (TdP), a form of polymorphic ventricular tachycardia, spurred on by prolonged repolarization, is one such example. iPS cell mutations in potassium channels KCNQ1 and KCNH2, responsible for Type I and Type II LQTS respectively, exhibit multiple elements of the disease including cardiomyocytes with prolonged field potential depolarization, action potential duration and diminished inward potassium current resulting from trafficking defects76-80. Drug screens to identify novel therapeutics have shown that novel therapies including N-[N-(N-acetyl –L-leucyl)-L—leucyl]-L-norleucine (ALLN) were able to improve trafficking of the KCNH2 and complement the phenotype of LQT281. Recapitulation of sodium channel mutations (SCN5a) in LQT3 and calcium channel mutations (CACNA1C) in LQT8 similarly demonstrated aberrant action potential duration and increased after depolarization, a mechanism thought to underlying the initiation of TdP82-85. Notably the phenotype of LQT3 was treated successfully with a sodium channel blocker, mexilitene, which mirrors clinical practice and demonstrated the ability of this cell to mimic physiologically relevant outputs of the disease state86. Cardiomyopathies There are a number of inherited disorders affecting the sarcomere that have been modeled using iPS cells. Mutations resulting in dilated cardiomyopathy have been elucidated recently and iPS cells from patients with those diseases have recapitulated many biological elements of the disease. iPS derived cardiomyocytes generated from a family with dilated cardiomyopathy harboring the R173W mutation in TNNT2, exhibit sarcomeric disorganization, Z body pathology, reduced force generation, calcium dysregulation and reduced tolerance to beta adrenergic signaling87-88. Overexpression of SERCA2a attenuated this phenotype, with improved calcium handling and signaling through PKA. Beta adrenergic

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blockade with metoprolol and phosphodiesterase inhibition with milrinone and two experimental compounds similarly showed an improvement in the phenotype. Similar phenotypes were also described using iPS cells with mutations in other genes linked to dilated cardiomyopathy, including LMNA/C, DESMIN and RBM2089-91. Mutations in hypertrophic cardiomyopathy have been well described and iPS lines derived from patients with those mutations have similarly recapitulated numerous biological aspects of the disease. Mutations in myosin heavy chain 792-93 and myosin binding protein C394 have resulted in iPS derived cardiomyocytes with hypertrophic sarcomeric structure, increased intracellular calcium and electrical dysrhythmias. Treatment of these cells with beta adrenergic and L-type calcium channel blockade reversed the phenotype. Gene expression analysis of these cells enabled mechanistic insights into the signaling pathways (e.g Wnt, notch and FGF signaling) associated with the hypertrophic state92.

Furthermore, it confirmed that aberrant calcium

handling contributes to the pathogenesis of arrhythmogenicity in this tissue and demonstrated therapeutic potential with calcium channel blockade. LEOPARD syndrome (lentigenes, electrocardiographic abnormalities, ocular hypertelorism, pulmonary valve stenosis, abnormal genitalia, retardation of growth and deafness) is a multisystem inherited RAS-opathy due to mutations in PTPN11, which encodes an important lipid phosphatase upstream of RAS activation.

Hypertrophic cardiomyopathy is the most

important life threatening cardiac abnormality in this syndrome and iPS cells generated from patients exhibit increased sarcomeric area organization consistent with a hypertrophic phenotype95. Furthermore, studies have shown increased activation of the RAS MAPK pathway in these cells as well as increased nuclear localization of NFAT transcription factors, leading to insights into the molecular changes and pathways in cardiac physiology that are affected by mutations in this phosphatase. Mutations in desmosomal proteins, specifically plakophilin PKP2, cause a rare right ventricular cardiomyopathy known as arhythmogenic right ventricular cardiomyopathy or dysplasia,

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characterized by RV fibrosis, fatty infiltration, right ventricular failure and ventricular tachycardia. Cardiomyocytes with mutations in this gene mimic the disease and exhibit defects in metabolic pathways that balance lipogenesis and glycolysis resulting in increased cell death and sarcomeric disorganization, specifically at the sarcomere96-97. Metabolic Pathways Disorders of metabolism affect the heart in two distinct ways. The first one is dysregulation of energy consumption. The heart is a highly aerobic organ and disorders affecting the mitochondria and aerobic respiration have deleterious effects on heart energetics. Barth Syndrome is a mitochondrial disease characterized by mutations in the Tafazzin gene that leads to altered cardiolipin processing and deformation of the mitochondrial structure.

iPS

cardiomyoyctes derived from patients with Barth Syndrome exhibited disorganized sarcomeres with diminished force generation and metabolic deficiencies, a phenotype that was complemented by reconstitution of the wild type allele98. The second one is misprocessing of metabolic intermediates leading to accumulation of these intermediates in either the myocytes or tissue interstitium. The result of this infiltration is usually a restrictive phenotype whereby sarcomeric function is intact but compliance of the organ is diminished by mechanical interference of the accumulated substrate. At the cellular level however, these forms of cardiomyopathies are poorly understood and the generation iPS cells from individuals with these disorders has led to mechanistic insights.

Mutations in the

lysosomal glycogen hydrolase α-glucosidase lead to Pompe Disease and accumulation of lysosomal glycogen.

iPS derived cardiomyocytes exhibit intact sarcomeric function as

expected, but also had increased lysosomal size, glycogen and a defect in glycan metabolism99. As in Barth Syndrome, expression of the wild type allele of the glucosidase was able to reverse the phenotype100.

Preclinical Drug Testing with iPS Cells

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Initial toxicity testing is currently performed in cell lines, animals and healthy volunteers. However, in many cardiac therapies, the application of drugs is mostly in a population with a disease state that may or may not interact with the pharmacology of the drug to generate an unheralded toxicity. A famous example of this was the drug cisapride, a serotonergic agonist that was a clinically efficacious promoter of gastrointestinal motility in such diseases as gastrointestinal reflux and gastroparesis101. Post marketing surveillance after cisapride was approved revealed rare instances of palpitation, TdP, ventricular fibrillation and death102. These were usually observed in patients with underlying cardiac disease and it was then recognized that cisapride prolongs the QT interval. Patients with prolonged QT intervals and heart failure were susceptible to the proarrhythmogenic properties of cisapride and it was pulled from the global market in 2000103. Electrophysiological studies revealed that cisapride was a potent blocker the potassium channel hERG, prolonging the action potential and essentially delaying repolarization104-105. Experiments with iPS cells revealed later that cisapride caused both early and delayed afterdepolarizations in iPS cells derived from patients with inherited LQT syndrome and hypertrophic cardiomyopathy, but not in normal iPS cells. A major advantage to iPS cells is the ability to determine toxicity profiles by preclinical testing of functional outputs that are more relevant to end-organ toxicity than standard assays that asses proliferation and viability in cell culture106-110. iPS cells can also provide mechanistic information by establishing novel models to understand already known toxicities in drugs.

A classic

example is doxorubicin, an anthracycline anti-neoplastic agent that is widely used and incredibly efficacious against a number of different tumor types but at the same time has showed dose dependent cardiac toxicity attributed to a number of possible mechanisms.

Burridge and

colleagues111 generated iPS cells from patients who developed cardiac toxicity and those that did not at the same doses and showed patient specific toxicity profiles which probed patient specific oxidative stress, DNA damage mitochondrial function and modulation of gene expression.

Remarkably, they demonstrated that iPS cells mirrored the sensitivity to

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doxorubicin from their patients they were derived from. This translated into patient specific molecular differences that reflected an underlying predilection for toxicity at a number of levels to doxorubicin. This bolsters the argument for using these cells as a patient model, with the ability to capture complex pharmacogenomics nuances at the cellular level that lead to important clinical toxicities. These findings affirmed the clinical experience and demonstrates how iPS cells and banks of iPS cells derived from patients with inherited diseases can be used to screen for drug toxicities that may not be detected until those drugs are prescribed beyond the boundaries of a very specific and narrow trial population.

The (new) Human Model A tenet of work with cell monolayers in biological sciences is the assumption that they reflect some aspect that is scientifically relevant of the derived tissue or disease model. ] Cell culture in two dimensions has numerous limitations. The first one is in the dissimilarity between the physiological interface of standard tissue culture versus three dimensional tissue systems. There is non-physiological diffusion of drugs in two-dimensional culture which poorly predicts serum concentrations that will determine eventual clinical efficacy and toxicity.

Drug

metabolism and excretion in tissue culture does not represent those processes at the organ level that link the kidney, liver and gut as the master regulator of drug absorption and excretion. There is also a loss of cell-cell and cell-matrix interactions. In terms of mechanical loading, the stiffness of tissue culture dishes is not the same as in the natural tissue milieu112. Furthermore, oxygen concentration is poorly modeled, and tissue culture systems at “normoxia” fail to account for oxygen diffusion and hypoxia conditions in native tissues113-114. In essence, there are no true human structures that are two dimensional, or attached to polystyrene and completely exposed to a complement of full nutrients and the drug of interest. In terms of toxicity outputs, two-dimensional systems have similarly poor representation of actual toxicities

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in clinical practice. As demonstrated in the case of cisapride, fatal side effects can often have nuanced phenotypes at the cellular level. Standard outputs of cell death or proliferation do not adequately recapitulate actual clinical toxicities that affect patients. This disconnect has led to artificial and non-physiological responses to numerous drugs, demonstrating poor mimic of cellular responses in a biological synthetic milieu. The transition from historical assays of cells in a two dimensional system to that of more relevant three dimensional system has significantly improved the fidelity of the morphological, phenotypical and functional characteristics of cells compared to their counterparts in human tissues72. This has progressed to the point that representative tissue units of organs can be generated to capture the structure, cellular heterogeneity and function of in vivo tissue. Importantly, advances in biomaterials have reconstituted an important and overlooked interaction between cells and the surrounding extracellular matrix.

Likewise, vascularity of

tissues through engineered networks is now feasible, allowing us to study fluid mechanics and tissue perfusion115-116. The ability to recreate physiological meaningful three-dimensional representations of different tissues and organs has been a timely advance in tissue engineering. With the obvious ethical consideration of using actual live humans or human tissue for early discovery and toxicity studies, in vitro organ-on-chips platforms are being refined to mimic physiological aspects of actual human tissue. The use of these platforms has been accelerated greatly by our increased ability to control the fate of stem cells and to combine difference cell types to reconstitute complex cellular relationships in various organs. Significant to drug testing, linking organs on chip together to form a human on a chip system is now being developed with some success117-118. This new model of human physiology combined with the ability to generate stem cell populations from essentially any individual, has huge significance for personalized medicine and the potential to generate human clinical trials in vitro at the preclinical stage (Figure 2). Within this framework lies the overarching goal of producing

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a minimally functional tissue unit that captures the necessary physiological complexity that can predict efficacy, safety and mode of action of a drug.

Engineering Human Cardiac Muscle As heart disease is in a large part due to the inability of the heart to generate new cardiomyocytes to replace either necrotic or pathological tissue, engineering of human heart tissue has been motivated by the need to repair damaged myocardium. Fortuitously in doing so, a novel platform for drug efficacy and toxicity testing has simultaneously been developed. A fundamental challenge has been to generate a microscale platform that is able to form and support the smallest unit of myocardium that replicates the molecular, electrical and mechanical properties of that tissue. In turn, this challenge involves a number of technical hurdles. The first one is scalability. Drug screens require high throughput to assess large numbers of candidate compounds. Microtechnologies must then be employed to generate the smallest possible unit of functional myocardium to minimize both cells and materials119-120. The second one is the integration of microfluidics to provide nutrients and oxygen or through fabricated endothelial beds that mimic vascular structures116. The diffusional penetration of oxygen limits the size of the microtissue significantly to under 100 µm in any dimension.

Lastly, there is the generation of mature

myocardium. ES and iPS cell differentiation protocols usually yield highly immature, fetal like cardiomyocytes121-122. A number of maneuvers have been developed to promote maturation. Modulation of the extracellular matrix, specifically using collagen I and decellularized extracellular matrix (ECM) from porcine hearts, has been shown to improve the maturation of ESCs123. Mechanical conditioning improved cell alignment, and the length and thickness of sarcomeres124. Chronotropy was enhanced as was the conduction velocity. Similarly, electrical stimulation has been shown to stimulate sarcomere maturation, gap junction expression and alignment and gene expression profile125. Incorporation of electrical stimulation into platform

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design can additionally control frequency and force of contraction of cardiac organoids. Combined mechanical and electrical stimulation has the ability to mimic disease states and to investigate drug interactions in the context of cardiac function.

As cardiomyocytes are

mechanical units and their morphology is intricately connected to their function, efforts to conform cardiomyocytes to certain geometries that mimic physiological conditions, known as micropatterning, has yielded improved sarcomeric organization, cell-cell junctions and contractile force126-128.

In micropatterning, two and three dimensional topographies are

engineered into a scaffold and act to constrain the dimensions of the cell to that specific pattern. Incorporating micropatterning into differentiation protocols has yielded significant improvements in

cardiomyocyte

differentiation

and

maturity

demonstrating

the

importance

of

the

microenvironment and its architecture on cardiac ontogeny129-130. Supply of nutrients, removal of waste and delivery of drugs is a special consideration with threedimensional tissues. Diffusion has a limited capacity to serve the metabolic needs of complex tissue structures and it is difficult to model drug diffusion across a structure to correlate outputs of efficacy and safety with concentration gradients within the tissue. For prolonged tissue survival and functionality, vascular networks have been designed within myocardium to enhance transport to and from the cells within the tissue. Vascularization has shown improvements in viability and cardiomyocyte function when compared to unvascularized tissues131. Endothelial cells likely have an additional ability to improve cardiomyocyte function and stability through advantageous cell-cell interactions and paracrine effects132.

The utilization of pre-formed

vascular networks has the added advantage of mimicking actual drug delivery as well as a means of connecting multiple tissues together. Because cardiac microtissues mimic the structural and functional characteristics of native heart tissue, more pertinent and clinically relevant surrogates can be measured to gauge efficacy and safety133. The microtissues exhibit mature electro-mechanical coupling of ion channel based depolarizations with sarcomeric function. Outputs that delineate the characteristics of the action

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potential, force generation (inotropy), relaxation (lusitropy) and heart rate (chronotropy) can all be

measured.

Cells

from

microtissues

can

be

dissociated

and

more

thorough

electrophysiological assays such as patch clamp, gene expression analysis, tissue ultrastructure and metabolic profiling can all be performed to give an in depth evaluation of myocardial properties. The combination of these elements can give meaningful insights into drug development for a number of cardiac diseases such as heart failure, ischemic heart disease, and arrhythmias. Furthermore, there is an obvious set of relevant measurements that would be most informative when screening drug toxicities in the heart: cell death due to direct damage (such as following the administration of doxorubicin), mitochondrial or metabolic dysfunction (also following the administration of doxorubicin), arrhythmogenicity (following the administration

of

cisapride),

sarcomeric

dysfunction

(following

the

administration

of

trastuzumab) and calcium handling impairment (following the administration of tricyclic antidepressants). Assays measuring these outputs are available, facile and most importantly, scalable for high throughput platforms134-135.

Multiple Human Tissue Types on a Chip Clinical endpoints involve complex interplays between organ systems that impact both efficacy and toxicity profiles. Take for example clopidogrel. In terms of clinical benefit, prevention of thrombosis is the likely mechanism that occurs at the level of the coronary vasculature. Bleeding from clopidogrel, however, is often a cryptic event arising from injury of a vascular bed of another organ such as the GI tract, the eye or the brain. Additionally, there are humans with an allele of the cytochrome P450 2C19 oxidase in the liver that fail to metabolize the clopidogrel prodrug into the active thienopyridine which inhibits platelet reactivity136. These patients have resistance to clopidogrel and increased thrombotic effects of the drug compared to those without that allele. This is a typical example of the fact that there are many human to human variations in metabolism, absorption, excretion and genetic variants that modulate drug

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response. Attempting to model such complexity at the preclinical stage is extraordinarily difficult and likely accounts for up to 60% of late stage drug development failures137. Additionally, our understanding of drug mechanisms is limited, as exemplified in the case of cisapride and its unheralded effect on a potassium channel, and our ability to predict toxicities in other major organs or physiological systems is likewise limited. Thus we need new systems to better model and predict this complexity prior to going to clinical trials. The integration of multiple tissue types addresses a number of these issues. Microtissues can be derived from a single cell source and the combined using a perfusable vascular network to yield a modular system where organoids can be swapped in and out to generate the desired physiological interactions. In the HeLiVa platform being developed in our lab, a single iPS line with CRISPR-Cas9 inserted color specific reporters for each lineage, is used to generate liver and cardiac microtissues connected by iPS derived endothelial cells lining microfluidic channels138. Integrating liver metabolism and cardiac function is an incredibly important step, considering that many drug toxicities are actually due to the metabolites and not the drug themselves. Modeling this complicated interplay of the drugs and tissues while maintaining a platform for high throughput screening has the potential for making a fundamental leap in our ability to predict real patient toxicity profiles. The HeLiVa platform and others like it should make an important advance in the ability of these microtissue systems to accurately predict human toxicity. Also, by using iPS cells, this system has a versatility of genetic manipulation, and can be used to capture the effects of gender and broad classes of genetic backgrounds. Humans have quite variable metabolism of drugs depending on certain cytochrome polymorphism and this can actually now be modeled with either deriving iPS lines from humans with different alleles versus making allelic modifications within the same line.

In silico Human Trial

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Clinical drug efficacy, as measured in clinical trials, is a complex combination of targeting a mechanism in a population at risk for an event and the specific rate of the event in that population. There are rates of harm and benefit that are specific to the risk of the population being studied and thus drug approval is tailored to specific populations that were studied in trials.

Net clinical benefit dictates that rate of unacceptable harm imposed by a drug cannot

exceed the rate that the benefit occurs. As an example, the clinical benefit for clopidogel was proven in patients who have severe cardiovascular disease. They have such high event rates that a benefit of taking daily clopidogrel could be detected within around 9 months of a population starting the medication compared to placebo.

This outweighed the amount of

serious bleeding that occurred within that time period. If clopidogrel had been studied in healthy teenagers, one would see essentially total harm since cardiovascular events almost never occur in that age group, and if they do, they are not mechanistically linked to platelet reactivity. It would seem premature at this stage to design platforms that assess efficacy in a Bayesian manner as randomized controlled trials do. But what about toxicity? A large element underlying the risk of toxicity lies in genetic variation that modifies absorption, metabolism, pharmacodyamincs and off-target effects. Platforms like HeLiVa do bring the potential for generating high throughput systems that integrate drug metabolism. Genetic heterogeneity could be layered as an extra dimension in this platform, by utilizing large banks of iPS lines representing a broad genetic range of humans-on-a-chip (Figure 2). One could imagine having thousands of iPS lines which span polymorphisms and allelic variations that could be used as a core testing platform for all drugs in terms of end-organ toxicities, integrating tissues like liver to model metabolism and bowel epithelium to model absorption. In certain diseases where there is likely an inherited component, such as early onset cardiomyopathy, disease-specific cohorts could be generated for specific and refined drug testing. In these smaller and more specific cohorts where genotype and phenotype have clear linkage, the variance of efficacy could also be addressed. There are a number of extraordinary

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technical hurdles that cannot be understated - such as being able reliably and reproducibly differentiate cells to generate similar organoids from each individual139. One of the drawbacks of such an approach is that number of cell lines needed to capture population “diversity” would be different for every drug and based on the combination of allelic frequencies that generates toxicity and the variance of outputs from the system. For instance, if a drug generated a cardiac toxicity associated with a genotype incidence of 0.01, then 100 human lines would be needed to pick up one toxicity event. However, if the toxicity readout of the platform has a wide confidence interval with significant variability, then the number of cell lines would have to be expanded in order to achieve statistical power to detect that toxicity. There is also the issue of what frequency of toxicity is tolerable. That wholly depends on the clinical benefit imparted by that drug. Clinicians balance risk and benefit and the tolerance for toxicity is obviously more broad if is the there is greater clinical need or greater clinical benefit. These technical hurdles are quite steep. But overall, if we can move towards diversify platforms genetically, this would be a large step ahead in assessing the potential of a drug to be efficacious or cause harm in a large human population prior to actual clinical trials.

Precision medicine At the individual level, the utilization of human-based scalable iPS platforms has the potential for tailoring the therapy and improving diagnostics. A major practical problem encountered by clinicians is that we treat patients based on the mean results of large populations studied in randomized controlled trials. Inherent in this is the paradox that many patients in the treatment arm did not derive any benefit or even experienced harm from an intervention that is on average considered positive on a large population (Figure 3). This is one of the greatest challenges for treating individual patients like a study population. Physicians currently have no tools to identify

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which patients are most likely to derive benefit. The end result is that physicians often have to try and use multiple therapies targeting the same process on a single patient to generate the desired clinical effect.

This exposes the patient to added harm and adverse drug effects.

Similar to PDX models for testing individual tumor susceptibility, iPS based platforms provide the opportunity to bring precision medicine to a whole new ex vivo system for screening therapies. Generating an integrated organoid platform from a patient’s iPS cells is feasible, safe, scalable and would allow high throughput drug testing on specific physiological outputs that could be modeled to parallel desired clinical effect. This would help guide physicians to therapies a patient may be more susceptible too, preventing polypharmacy and adverse drug events. iPS cell based platforms can also provide significant contributions to the diagnosis and prognosis of genetic diseases.

This is best exemplified in the case of inherited

cardiomyopathies in two separate ways. First is to help identify affected family members in genotype-negative diseases. In the case of clearly inherited dilated cardiomyopathy, our ability to find an inherited mutation is usually less than 50%. Thus the ability to predict, and monitor affected family members is hampered quite significantly. IPS cells could be a valuable tool in this respect, if they can reconstruct a measurable component of the cardiomyopathy and be used as a surrogate to determine which family members are affected.

A second clinical

situation where there may be significant utility for iPS cell based platforms is in patients who are genotype

positive

but

phenotype

negative.

This

is

sometimes

found

in

inherited

cardiomyopathies as well as inherited dysrhythmias such as Brugada and LQTS. The risk of sudden death is difficult to ascertain in mutation-positive but clinically unaffected patients. iPS cells could be a fantastic tool to determine susceptibility to malignant arrhthymias or cardiac dysfunction. For instance, in the case of LQT, iPS cells could be derived from phenotype negative family members and then used to test susceptibility to TdP in the presence of classic QT prolonging drugs. This would be a significant contribution to not only our ability to help

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stratify risks and treat patients who are phenotypically ambiguous, but would also lead to deeper understanding of the disease penetrance and the treatment of certain disease states. Conclusion Animal models have served to advance our understanding of human physiology. At the same time, as predictor of therapeutic success, animal models have fallen short for a number of reasons. It is impossible for us to take the theory of homology to the limit and use humans to explore target mechanisms and perform large-scale drug screens. However, the confluence of tissue engineering and cell biology has allowed us to generate human based platforms that could perhaps serve as a surrogate of certain physiological functions. With integrated tissue systems combined with genetic diversity, there is real potential to better predict efficacy and toxicity in humans. This will also impact diagnostics, prognostication and tailored therapeutics. The generation of humans-on-a-chip is paradigm-shifting, and preclinical trials in silico may guide the choice of therapeutics with more accuracy and chance of success.

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Figure 1: Physiologic comparison between humans and mice41, 140.

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Figure 2:

iPS Cell Based Drug Development.

Page 30 of 42

In classic drug discovery (right), high

throughput compound screening occurs up front with cell lines which are then narrowed to testing in animal models. Promising candidates are then used in humans at first for safety and pharmacologic endpoints.

Ultimately, a drug is tested in humans with a disease or target

characteristic in randomized controlled trial (RCT) if possible which then will lead to final determination of efficacy and safety. An idealized iPS cell model for drug discovery (left) would start with the generation of a large bank of iPS cells representing a target population. These iPS cells would then be differentiated into organoids and tested in microtissue platforms. High throughput compound screening using surrogate physiologic outputs of efficacy or safety would

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then lead to the identification of promising candidates which can then be fed back into the classic pipeline. The goal of this would be to pick up potential candidates that would have been missed in cell lines and animal models as well as identify possible toxicities early on prior to testing in humans.

Figure 3: iPS Cell Based Personalized Medicine.

In a randomized control trial, target

populations meeting specific criteria are tested with either the intervention/therapy or a placebo. The mean response to the therapy (efficacy) and toxicity profiles (safety) combine into net clinical benefit or net clinical harm. However, not all patients in a cohort respond the same way, and though on a population level, a drug may generate net clinical benefit, there are patient in the treatment cohort who did not have a favorable response (shaded part of the distribution

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curve of the therapy group). Though a drug may be approved on the basis of such a trial, there are going to be certain individuals who do not respond. This is the essence of the breakdown between population medicine and individualized medicine.

iPS cells have the potential to

overcome this shortcoming. By generating organoids and integrated tissue systems for drug testing, iPS cells based systems can be used to screen for drug response (represented as red on the array) in a high throughput manner. This would then avoid direct human exposure to multiple drugs with multiple toxicities or efficacy failure in order to achieve the clinical endpoint. References 1. Ericsson, A. C.; Crim, M. J.; Franklin, C. L., A brief history of animal modeling. Mo Med 2013, 110 (3), 201-5. 2.

Enard, W., Mouse models of human evolution. Curr Opin Genet Dev 2014, 29, 75-80.

3. Uhl, E. W.; Warner, N. J., Mouse Models as Predictors of Human Responses: Evolutionary Medicine. Curr Pathobiol Rep 2015, 3 (3), 219-223. 4. Pippin, J. J., The Failing Animal Research Paradigm for Human Disease. Independent Science News 2014. 5. Hay, M.; Thomas, D. W.; Craighead, J. L.; Economides, C.; Rosenthal, J., Clinical development success rates for investigational drugs. Nat Biotechnol 2014, 32 (1), 40-51. 6. Hodgkin, A. L.; Huxley, A. F., A quantitative description of membrane current and its application to conduction and excitation in nerve. J Physiol 1952, 117 (4), 500-44. 7. Skrzypiec-Spring, M.; Grotthus, B.; Szelag, A.; Schulz, R., Isolated heart perfusion according to Langendorff---still viable in the new millennium. J Pharmacol Toxicol Methods 2007, 55 (2), 113-26. 8.

Zimmer, H. G., The Isolated Perfused Heart and Its Pioneers. News Physiol Sci 1998, 13, 203-210.

9. Bakkers, J., Zebrafish as a model to study cardiac development and human cardiac disease. Cardiovasc Res 2011, 91 (2), 279-88. 10. Bamford, R. N.; Roessler, E.; Burdine, R. D.; Saplakoglu, U.; dela Cruz, J.; Splitt, M.; Goodship, J. A.; Towbin, J.; Bowers, P.; Ferrero, G. B.; Marino, B.; Schier, A. F.; Shen, M. M.; Muenke, M.; Casey, B., Loss-offunction mutations in the EGF-CFC gene CFC1 are associated with human left-right laterality defects. Nat Genet 2000, 26 (3), 365-9. 11. Garg, V.; Kathiriya, I. S.; Barnes, R.; Schluterman, M. K.; King, I. N.; Butler, C. A.; Rothrock, C. R.; Eapen, R. S.; Hirayama-Yamada, K.; Joo, K.; Matsuoka, R.; Cohen, J. C.; Srivastava, D., GATA4 mutations cause human congenital heart defects and reveal an interaction with TBX5. Nature 2003, 424 (6947), 443-7. 12.

Wall, R. J.; Shani, M., Are animal models as good as we think? Theriogenology 2008, 69 (1), 2-9.

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13. Richardson, M. K.; Keuck, G., Haeckel's ABC of evolution and development. Biol Rev Camb Philos Soc 2002, 77 (4), 495-528. 14.

Greek, R., Money in Animal Based Research. Animal Rights 2010.

15. Blevins, S. M.; Bronze, M. S., Robert Koch and the 'golden age' of bacteriology. Int J Infect Dis 2010, 14 (9), e744-51. 16. Gould, S. E.; Junttila, M. R.; de Sauvage, F. J., Translational value of mouse models in oncology drug development. Nat Med 2015, 21 (5), 431-9. 17. Cai, C. L.; Liang, X.; Shi, Y.; Chu, P. H.; Pfaff, S. L.; Chen, J.; Evans, S., Isl1 identifies a cardiac progenitor population that proliferates prior to differentiation and contributes a majority of cells to the heart. Developmental cell 2003, 5 (6), 877-89. 18. Oka, T.; Maillet, M.; Watt, A. J.; Schwartz, R. J.; Aronow, B. J.; Duncan, S. A.; Molkentin, J. D., Cardiac-specific deletion of Gata4 reveals its requirement for hypertrophy, compensation, and myocyte viability. Circ Res 2006, 98 (6), 837-45. 19. Sicinski, P.; Geng, Y.; Ryder-Cook, A. S.; Barnard, E. A.; Darlison, M. G.; Barnard, P. J., The molecular basis of muscular dystrophy in the mdx mouse: a point mutation. Science 1989, 244 (4912), 1578-80. 20. Bulfield, G.; Siller, W. G.; Wight, P. A.; Moore, K. J., X chromosome-linked muscular dystrophy (mdx) in the mouse. Proc Natl Acad Sci U S A 1984, 81 (4), 1189-92. 21. Long, C.; McAnally, J. R.; Shelton, J. M.; Mireault, A. A.; Bassel-Duby, R.; Olson, E. N., Prevention of muscular dystrophy in mice by CRISPR/Cas9-mediated editing of germline DNA. Science 2014, 345 (6201), 1184-8. 22. Shultz, L. D.; Brehm, M. A.; Garcia-Martinez, J. V.; Greiner, D. L., Humanized mice for ee system investigation: progress, promise and challenges. Nat Rev Immunol 2012, 12 (11), 786-98. 23. Olson, A. K.; Ledee, D.; Iwamoto, K.; Kajimoto, M.; O'Kelly Priddy, C.; Isern, N.; Portman, M. A., C-Myc induced compensated cardiac hypertrophy increases free fatty acid utilization for the citric acid cycle. J Mol Cell Cardiol 2013, 55, 156-64. 24.

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25. Thomson, A. W.; Turnquist, H. R.; Raimondi, G., Immunoregulatory functions of mTOR inhibition. Nat Rev Immunol 2009, 9 (5), 324-37. 26. Horrobin, D. F., Modern biomedical research: an internally self-consistent universe with little contact with medical reality? Nat Rev Drug Discov 2003, 2 (2), 151-4. 27. Shanks, N.; Greek, R.; Greek, J., Are animal models predictive for humans? Philos Ethics Humanit Med 2009, 4, 2. 28. Hunter, A. J., Have animal models of disease helped or hindered the drug discovery process? Ann N Y Acad Sci 2011, 1245, 1-2. 29. Shuster, E., Fifty years later: the significance of the Nuremberg Code. N Engl J Med 1997, 337 (20), 1436-40. 30.

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For Table of Contents Use Only The shortcomings of animal models and the rise of engineered human cardiac tissue Barry Fine and Gordana Vunjak-Novakovic

Synopsis: This figure represents a new paradigm in drug development in which genetically diverse stem cells are used to generate tissue platforms for high throughput drug testing prior to human trials.

Tissue Engineering

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Shortcomings of Animal Models and the Rise of Engineered Human

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