Evidence of repurposing drugs and identifying contraindications from

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Evidence of repurposing drugs and identifying contraindications from real world study in Parkinson’s disease Yilin Tang, Ke Yang, Jue Zhao, Xiaoniu Liang, and Jian Wang ACS Chem. Neurosci., Just Accepted Manuscript • DOI: 10.1021/acschemneuro.8b00456 • Publication Date (Web): 31 Jan 2019 Downloaded from http://pubs.acs.org on February 3, 2019

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ACS Chemical Neuroscience

Evidence of repurposing drugs and identifying contraindications from real world study in Parkinson’s disease

Yilin Tang#, Ke Yang#, Jue Zhao, Xiaoniu Liang, Jian Wang*

Department of Neurology and National Clinical Research Center for Aging and Medicine,

Huashan Hospital, Fudan University, Shanghai 200040, China

# These

#

authors contributed equally to this work.

Correspondence to: Dr. Jian Wang, Department of Neurology and National Clinical Research

Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China.

Phone: 86-13321934789, Fax: 86-21-52888163, E-mail: [email protected]

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ABSTRACT There is great unmet need in discovering novel treatment for Parkinson's disease (PD) and identifying the new agents potentially causing drug-induced parkinsonism. New indications and contraindications of drugs are typically approved following rigorous randomized controlled trials (RCTs) evaluation. However, RCTs have their inherent limitations, since they are usually conducted in ideal conditions, with high cost and limited follow-up periods. In the past decade, large cohort studies with long follow-up outcome data was derived from PD database in a real-world setting. Studies based on real world data (RWD) can help to augment and extrapolate data obtained in RCTs and provide information about the safety and effectiveness of a medication in heterogeneous, large populations. In the present review, we focus on the published real world studies designed to develop new treatment strategies for repurposing drugs and identifying contraindications for PD. We also outline the challenges and limitations in these studies. Subsequently we introduce PaWei APP platform which hopefully contribute to facilitate PD management and address real-world problems associated with PD. Better understanding of RWD collection and analysis is needed if RWD is to be achieved as its full potential.

Key Words: Parkinson's disease; repurposing drug; contraindication; real world study; randomized controlled trial


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1. Introduction Parkinson’s disease (PD) is a complex and heterogeneous neurodegenerative disorder. Despite great efforts invested into the searching for therapies, there remains no curative treatment. There are great unmet needs in novel symptomatic and disease modifying treatment of PD. Given the drug development is an increasingly time-consuming, expensive, and risky process, drug repurposing, the identification of novel therapeutic indications for approved drugs, has the potential to expedite route for drug discovery. To date, drug repurposing has often been approved on the basis of their efficacy in randomized controlled trials (RCTs). Although RCTs are still considered to be the qualifying factor with highest evidence hierarchy in assessing the safety and efficacy of any drug, the high cost and limited follow-up periods make it challenging to evaluate long-term efficacy, and because of narrowly defined populations, they might not provide the efficacy of an intervention in real-world practice. Identifying the new agents potentially causing drug-induced parkinsonism or increasing risk of developing PD is also urgently needed, since the parkinsonism including idiopathic PD should avoid the exposure of any medications with those risks. However, it is inappropriate to conduct RCTs to screen all the previously used drugs of parkinsonian patients because of the ethical issues. Real world data (RWD) brings us opportunity to solve above issues. RWD was defined as all data collected from sources other than RCTs. RWD can be analyzed in real world study (RWS) to produce real world evidence (RWE) 1. The development of information-processing technology has increased the efficiency of data collecting,



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sharing and analyzing, which favored RWS over RCTs. As an important supplement, RWS can provide valuable information about the safety and efficacy data in a large heterogeneous

population,

compromising

the

drawbacks

of

restricted

and

unrepresentative population of RCTs. Here, we firstly review the current studies designed to identify the new indications and contraindications of drugs for PD. Secondly, we explore how RWD is being utilized in repurposing drugs and identifying contraindications. Finally, we introduce PaWei APP platform which potentially contribute to create novel and faster approaches to advance disease understanding and drug development.

2. Repurposing drugs for PD Drug repurposing, also referred to as drug repositioning or reprofiling, is the process of identifying new uses for existing drugs outside the scope of original clinical indication 2.

As compared to traditional strategy to develop therapies, the cost and timelines for

repurposed drugs are abbreviated. Moreover, the data on safety and tolerability are already available in approved medications. This expedites clinical trials and reduces the risk of failure due to adverse side effects or poor pharmacokinetics. Repurposing drugs could be a promising and efficient strategy in developing novel therapy for PD. During long course of the disease, patients with PD are always accompanied with various comorbidities. According to a survey, the most frequent comorbidities were hypertension (34%), diabetes mellitus type II (T2DM) (15%) and hyperlipidemia (14%) 3. Connections between PD and these comorbidities have revealed novel targets for drug


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repurposing 4. More importantly, medications for these comorbidities may interact with disease pathogenesis and offer promising disease modifying effect. In fact, there have already been amounts of preclinical and clinical studies focused on the existing medications for PD comorbidities. Here we highlight these promising agents in the most frequent comorbidities in PD Anti-diabetic agents Exenatide, the synthetic version of exendin-4, is an agonist for Glucagon-like peptide1 (GLP-1), and is licensed for the treatment of T2DM 5. Increasing number of preclinical works suggest that exenatide may provide neuroprotective effect on PD 6-11. As a proof of concept, an open-label trail was launched

12,

and motor and cognitive

assessments were improved significantly after 12-month exposure in the exenatide group compared with the control group, which sustained after additional 12-month washout period. In another recent published RCT study 13, it also revealed a significant advantage on the UPDRS-III score, and sustained 12 weeks after exenatide was discontinued. In the two exenatide clinical trial, wash-out designs were applied to eliminate any potential symptomatic effects from disease-modifying effects. However, a long washout period with several months or longer, could be confounded by the progressive nature of PD, and risks high levels of patient dropout. As a neurodegeneration, disease duration of PD always lasts for decades. Neither wash-out nor delay-start design can observe long enough time to replicate the course of disease progression. Moreover, the neuroprotection effects on PD could possibly be multi-dimensional, from motor to non-



motor aspects. A bunch of scales should be finished if the researcher hesitates to miss any possibility of neuroprotection. Even though, the benefit can be too subtle to be detected during the observation period of a clinical trial. That’s why using traditional strategy to evaluate repurposed neuroprotective drug is still costly, risky and definitely uncomplete. Anti-hypertension agents Though evidence on association between hypertension and risk of PD is conflicting 14, anti-hypertension therapies might be repurposed for disease modifying indication based on various preclinical and clinical studies. Among which, calcium channel blockers (CCBs), angiotensin converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs) are most promising repurposed drugs with either epidemiological or laboratory evidence. Epidemiological studies have shown that use of CCBs was associated with a reduced risk of developing PD 15-18. Isradipine, a kind of CCB of dihydropyridine, is being tested as a potential disease-modifying intervention in de-novo untreated PD by a 36-month phase 3 RCT(STEADY-PDIII) 19. The expected completion date will be in early 2019. With robust preclinical and strong epidemiological data, as well as ongoing RCT with longest duration ever proposed for a study in de-novo population, isradipine is thought to be the most promising CCB in disease-modifying treatment of PD. In addition, current evidence for the association between the type of CCB use and the risk of PD is not conclusive. It is not likely to launch clinical trials for all possible CCBs and to follow as long as 36-month.


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Increasing preclinical evidence suggest that the nigrostriatal renin-angiotensin system (RAS) may play an important role in the process of inflammation and oxidative stress in the dopaminergic neurons 20, which can be inhibited by ACEI and ARB. Therefore, interfering with brain angiotensin may constitute an effective neuroprotective therapy for PD. Numbers of in vivo studies 21 have reported that ACEI captopril and perindopril, and the ARB losartan, candesartan and telmisartan have neuroprotective effect in PD animal models. However, existing epidemiological data about whether ACEI or ARB decrease the risk of PD remains controversial 15, 16, 22, 23. These preclinical findings have not been translated into clinical trials, neither. Drawing clues from RWS may help us to screen out most promising RAS drugs which can slow down the disease progression. Lipid lowering agents Previous clinical studies demonstrated controversial results about the potential of statins in disease modifying of PD, where positive, negative and not-related association of statins and PD risk were all reported. Several epidemiological studies and metaanalysis discovered of significant reductions in PD risk among statin-users

24-27.

Comparing to hydrophilic statins, lipophilic statins are considered to have stronger protective effects on the incidence of PD. In a prospective cohort study, risk reduction was only observed in the simvastatin group, rather than hydrophilic statins 28. Lee and colleagues found that continuation of lipophilic statins like simvastatin and atorvastatin significantly reduced the risk of PD 29. However, complete opposite result was revealed in another retrospective case-control study where lipophilic statins surprisingly increased the risk of PD 30. Controversial clinical results make it a dilemma of statins’



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repurposing for PD. Therefore, a 26-month RCT (PD STAT, 2016) evaluating the disease modifying effect of simvastatin is being proceed in UK, expecting to be finished in 2020. Although with high evidence hierarchy and cofounder-controlling ability, one major concern of RCT is that it may take longer to induce the disease modifying result because the risk reduction effects of statins were relatively weak. Nevertheless, there is only limited time to maintain the cofounders under being controlled in RCT after the participants are recruited, which may make the results less convincing. RWS might be needed to add strong evidence about the association of statins and PD for the drugrepurposing project.

3. Identifying contraindications Identifying the new risk factors of PD or new agents potentially causing drug-induced parkinsonism is also urgently needed, since PD has diverse nature in term of etiology, and pathology, and of course prognosis. How to avoid any detrimental factors that could cause parkinsonism is very important for the long-term management of PD. Here we focus on several kinds of medicines used in the treatment of diabetes, hypertension, and depression. Risk factors of PD Among the common antihypertensive agents, beta-blocker was the very one associated with increased PD risk 31 instead of protective effects like ACEIs and CCBs 16, 22, 23, 31. However, the relative risk (RR) of beta-blocker to PD was low (1.24 - 1.28) 22, 31, and other case-control studies reported not-related association


15, 32.

After adjusting for

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demographics, smoking, and overall use of medical care, neither β2-adrenoreceptor agonists nor antagonists was found to be associated with the risk of PD.33 Controversial results could be explained by the lack of longitudinal data in case-control studies. It is more important to identify whether the usage of beta-blocker could accelerate or slow the disease course of PD. RCTs have been conducted, comparing beta-blockers with placebo for the adjuvant therapy in tremor of PD

34.

Nevertheless, none of the

RCTs reported the adverse event of worsened parkinsonism, probably because of the limited duration which was even less than 12 weeks. In terms of risk factors with moderate or mild effects on PD, it may take years before the existence of deleterious effect, which is unpractical for RCTs. Therefore, RWS could increase the positive findings of deleterious effects with longer follow-up duration, making it a strong and efficient way to identify the potential risk factor of PD. Agents of drug-induced parkinsonism Being different from risk factors, some agents are involved in a much closer and direct relationship with extrapyramidal symptoms (EPS), which referred as drug-induced parkinsonism. Trimetazidine (TMZ), an anti-ischemic agent used for angina pectoris, vertigo and tinnitus 35, 36, has been proven of its characteristics as parkinsonism-inducer. For decades since marketed, no association was revealed between TMZ and EPS until Marti Masso et al. published a series of cases of TMZ-induced parkinsonism in 2004 37.

In a retrospective study, thirty out of 130 TMZ-users reported drug-induced

parkinsonism or experienced worsen previous parkinsonism 38. All the extrapyramidal adverse reaction and worsened previous-diagnosed parkinsonism were disappeared



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after the withdrawal 38. It took decades before the discovery of TMZ-induced parkinsonism, which apparently with high incidence. Prolonged discovery process of the EPS side-effect caused by TMZ reminds us of the difficulties identifying new parkinsonism-inducers, which may leave amounts of risk drugs undiscovered. The term of “Drug-induced parkinsonism” means not only the temporal association but also a causal relation between the medications use and parkinsonism, which is easily confused in clinical setting. SSRI and SNRI, like Venlafaxine, Citalopram and paroxetine, were reported to be the top three antidepressants causing drug-induced parkinsonism

39.

However, whether the usage of antidepressants could affect the

prognosis of PD patients need further investigation. Even though there have been several case reports of worsened PD symptoms induced by antidepressants

40-43,

placebo-controlled clinical trials didn’t find any significant deleterious effects on motor function 44, 45. An RCT was organized to evaluate the safety and efficacy of paroxetine and venlafaxine in the treatment of depression of PD 46, reporting significant relief in depression without any side effects on motor symptoms. However, it is worth noticing that the follow-up duration was only 12 weeks, which might be too short before any deleterious effect could be induced. As we mentioned above, request for long follow-up duration could barely be met in RCTs. It also might be inappropriate to conduct RCTs because of the ethical issues. Therefore, RWS brings us opportunity to screen all the previously-used drugs of parkinsonian patients in a large data pool. In the future investigation of possible risk


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factor and parkinsonism-inducers, RWS would play an irreplaceable role considering its unique advantage.

4. Repurposing drugs and identifying contraindications in PD —— insights from real world studies In traditional evidence-based medicine, RCTs are considered to provide higher hierarchy of evidence than observational studies (Fig. 1). They unquestionably remain a powerful tool for drug developing. However, these trials are usually performed under restricted and ideal conditions, which have to comply with participant age, comorbidities or severity of disease. The limited follow-up periods and escalating development costs also make them unsuitable for long-term evaluation of safety and efficacy outcomes. Moreover, if the control subjects have poorer outcomes such as in identifying contraindications, it might be difficult to test this ethically in an RCT. In recent years, RWS is becoming an important way to build up the clinical evidence and identify the clues. It includes a wide spectrum of researches, ranging from observational studies to studies that incorporate planned interventions, whether with or without randomization at the point of care 47. A major driver for the integration of RWS into develop treatment strategies is understanding that RWS offer many advantages over RCTs: (1) Sample size is usually large: whilst important RCTs might have thousands of subjects, RWS might use a million; (2) The follow-up periods can be sufficiently long to assess long-term benefits and delayed risks of a drug. (3) RWS extend well to the general patient population with concomitant medication or multiple



comorbidities; (4) Groups are divided based on the patient's wishes or clinical reality, not necessarily random; (5) Treatment effects or outcomes based on the real clinical environment, so the external authenticity is better; (5) A variety of information on health care could be obtained from multiple sources, including electronic health records (EHRs), patient/disease registries, population health surveys, routinely collected administrative and insurance claims data, as well as emerging sources, such as data collected via mobile devices and apps 47-49. Today more than ever, patients, doctors and researchers have an active interest in RWS. Drawing clues from concomitant medications of PD patients together with longitudinal clinical data shed lights on repurposing drugs and identifying contraindications. Some existing drugs have already been investigated in RWS and have demonstrated therapeutic benefits (Table 1) or potentially detrimental for PD (Table 2). We highlight several kinds of medicines used in the treatment of diabetes, hypertension, and depression which are listed below. Anti-diabetic agents Several preclinical works and RCTs suggest that exenatide may provide neuroprotective effect on PD. Besides exenatide, whether other kind of GLP-1 agonist or Dipeptidyl peptidase-4 (DPP-4) inhibitors can show same disease-modifying potential are to be determined. A Swedish nationwide population-based case-control study identified 980 PD patients with T2DM and 4,900 controls with T2DM selected from the Total Population Register 50. They found that previous use of DPP-4 inhibitors (sitagliptin, vildagliptin, and saxagliptin) was associated with a significantly reduced


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risk of PD (OR:0.23, 95% CI 0.07 – 0.74). A larger sample size and longer follow-up study will be needed to confirm this observation. Metformin is also a widely-used antidiabetic drug, recently investigated and proposed to inhibit the development of L-DOPA-induced dyskinesia in a murine model

51.

A

Taiwanese population cohort study showed metformin-inclusive sulfonylurea therapy reduces the risk of PD occurring with T2DM

52.

800,000 participants were obtained

between 1996 and 2007 from the Taiwan National Health Insurance database. Those older than 20 years were classified by with (n = 64,166) or without (n = 698,587) T2DM, and whether any oral anti-diabetic agents (n = 41,003) or not (n = 23,163) was used. Hazard rations (HR) related to diabetes-free were 2.18 (95% CI 1.27 - 3.73) and 1.30 (95% CI 0.77 - 2.19) for T2DM without and with metformin-inclusive sulfonylurea therapy. However, another Taiwan cohort study showed long-term metformin exposure in elderly patients with T2DM may lead to the development of PD

53.

It evaluated the

effects of metformin exposure on the risk of PD in patients with T2DM by recruiting 4651 patients in the metformin cohort and a comparable number of controls in the Taiwan National Health Insurance Research Database. Increased risk of PD was observed in the metformin cohort during the 12-year follow-up (HR: 2.27, 95%CI 1.683.07). Results of the two cohort studies are contradictory. The reasons may be that: (1) Bias might exist on the diagnosed validity of these related diseases; (2) Possible confounders are not available, such as the lifestyle, family history, cigarette smoking and alcohol



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drinking. So larger scale, multiple centers and prospective RWS are required to further confirm the association. Beta-agonist and beta-blocker A population-based cohort study was done to analyze the correlation between exposure duration of salbutamol and propranolol, respectively the most commonly used β2 adrenergic receptor agonist and antagonist, and incidence of PD

54.

The study

population derived from Norwegian Prescription Database (NorPD) which included the total Norwegian population alive from 2004 to 2014 (n = 4.6 million). Cox regression confirmed the protective effects of Salbutamol (RR 0.66; 95%CI 0.58 - 0.76) and deleterious effects of propranolol (RR 2.20; 95%CI 1.62 - 3.00)

54.

The population

based longitudinal study with follow-up period up to six years has made up the drawbacks of traditional case-control studies, offering solid evidence consistent with lab-based results, at relatively low expense. Selective Serotonin Reuptake Inhibitor Whether there is a causal relationship between antidepressants and PD still need further identification. More and more evidence from large nested case-control study investigate in order to purify the relation between antidepressants and PD. To compare the risk of EPS between SSRI and other antidepressant drugs in PD patients, a retrospective study was performed using the French Pharmacovigilance Database 54. Among 76,640 case reports registered in the database between 1995 and 2000, there were 916 identified as patients treated with at least one antiparkinsonian drug, including 199 treated with antidepressant drugs. Only 9 patients were reported of EPS. There was no significant


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difference in the occurrence of EPS in terms of different classes of antidepressant drugs among patients treated with antiparkinsonian medicine. However, several studies had positive results. More than 1.5 million persons aged ≥ 65 years were analyzed in the Swedish Prescribed Drug Register 55. The result showed that crude odds ratio for the use of SSRIs in persons using anti-parkinson drugs compared with persons not using anti-parkinsonian drugs was 1.98 (95%CI 1.90 - 2.06). Positive results were also reported in another case control study, which was based on a large computerized database with clinical information from more than 3 million individuals in the UK

56.

It was conducted to explore the timing of the relationship between

initiation of antidepressant therapy and PD risk. They identified 999 PD patients and 6261 matched controls between 1995 and 2001. The RR of PD in initiators of antidepressant therapy was 1.85 (95% CI 1.25 – 2.75), comparing with non-initiators. The association was stronger during the first 2 years after initiation of antidepressant therapy (RR 2.19; 95% CI 1.38 – 3.46) than later (RR 1.23; 95% CI 0.57 – 2.67). Researchers made a conclusion that the initiation of any antidepressant drugs was associated with a higher risk of PD in the first 2 years after the start of treatment. Contradictory results of these RWS might due to several reasons: (1) They were retrospective nature and certain constraints imposed by the RWD used. For example, they can’t evaluate the accuracy of diagnoses or the use of antidepressants for purposes other than depression; (2) PD or non-PD patients with unrecognized depression cannot be identified using registry data; (3) Antidepressant adherence was not able to be assessed, only whether a prescription was filled. Thus the use of antidepressants should



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be further studied on the quality of treatment of depression in PD. Despite the many potential benefits, RWS are subject to limitations that must not be overlooked. There are still a number of issues with collecting real world data such as limited size of the databases, uncorrected bias and confounding factors and inability to accurately determine specific outcomes

57.

Larger data sets from databases and

registries and advances in statistical methodology with high quality data can mitigate some of the statistical limitations of RWS. Besides, in order to provide robust and reliable evidence, researchers should clearly understand the strengths and weaknesses of each data source. Protocols should be developed to maintain data integrity

58.

Considering these challenges, further understanding of RWD collection and analysis is needed if RWE is to achieve its full potential.

5. PaWei platform in the real PD world Mobile technology and widespread internet use offer new capabilities that can help to drive important aspects of chronic disease management and capture RWD at both an individual and population level. Under the wealth of RWD, there are numerous and various potential effects on chronic disease management, with the ability ranging from the monitor and assessment of symptoms to the determination of treatment effects in large-scale and patient-specific manner. Mobile applications might have the potential to develop into an indispensable tool to facilitate RWS in PD. In April 2017, we launched a platform named PaWei which contains iOS and Android smartphone applications for Chinese patients and doctors. It is designed to cover most


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of the aspects regarding the management of PD. As shown in Fig. 2, PaWei platform consists of some primary components. Its core, a cloud IT system, provides users all the necessary service communication and functions. For data processing and storage, compute power is also integrated in this system. This PaWei platform connects patients, doctors and researchers by the construction of communication and data transfer between the mobile applications and the cloud platform via the internet. Both doctors and patients can benefit from the platform. From the patient’s perspective, motor and non-motor self-evaluations via PaWei app could be a more effective method than home diaries. It offers a unique opportunity to assess the status of the patients, adjust medication schedules and personalize treatment without requiring physical interactions. Furthermore, it also provides educational materials on PD management and practical cases, thus narrowing the knowledge gap between doctors and patients. In this way, more personalized treatment was obtained as patients become active participants in the management of their disease. From the doctor’s perspective, PaWei app reduces the number of visits required as symptom evaluation can be carried out in patient’s home. This helps doctors more focused on the patients’ concerns and consequently spend less time obtaining or providing basic information. Moreover, it transfers all data collected to a central cloud infrastructure, while the doctors in the “members of PaWei” get free access to these data. Hence, PaWei platform collects RWD in PD while evaluating patients. Such RWD is a significant resource which reflects disease treatments, progression and outcomes under routine clinical practice. It plays a vital role in developing new treatment



strategies. Furthermore, a powerful and distinct feature of PaWei platform is the collection of longitudinal data which helps researchers to identify the etiology of PD by comparing PD patients and their healthy spouse as controls, as well as the factors determining the rate of progression by comparing the subgroups. The following sections display the primary functional modules available for patients (Fig. 3). Participant onboarding PaWei app can be downloaded for free through Android Market and Apple App Store. Enrollment is open to the patients diagnosed with PD and their family members (e.g. healthy spouse). Anyone interested in participating in the study as a healthy control is also allowed for the enrollment. Participants register by entering phone number and verification code. On the registration page, the minimum necessary information (name, identity card number, diagnosis, date of diagnosis and photo of medical records) is collected, to determine the participant’s eligibility by PaWei administrator. Informed consent After completing the registration, the web goes to an information or informed consent page, on which the participants are required to choose “agree” or “decline” the participation. There is also the option to share their data with qualified doctors and researchers. The PaWei consent is an information sheet (not requiring a physical signature) version of informed consent approved by the Human Studies Institutional Review Board, Huashan Hospital, Fudan University. The study is registered at the ClinicalTrials.gov database under registration number NCT03649503. PaWei APP


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plays a vital role in the RWS which can be designed to develop new treatment strategies for repurposing drugs and identifying contraindications for PD. Patient evaluation parameters Once the participant is enrolled, the platform collects an initial set of clinical parameters upon baseline registration, including patient’s initial diagnosis, current motor and nonmotor symptoms, disease duration, side of onset, previous and current treatment (duration and dosages in PD drugs, whether use drugs induced parkinsonism or other drugs), etc. Additional standard surveys used for PD assessment, Unified Parkinson’s disease Rating Scale (UPDRS II), Parkinson Disease Questionnaire 8 (PDQ-8) 59, , Non-motor Symptoms Scale (NMSS), Rapid Eye Movement Sleep Behavior Disorder Questionnaire (RBDQ), Beck Depression Inventory (BDI), Geriatric Depression Scale （GDS）and other scales. The participants should fill self-evaluation questionnaires at baseline as well as each season (90 days) for regular evaluation. Patients are invited to provide post-intervention feedback through app after clinic visits, including therapeutic efficacy and side effects. An optimal solution (e.g. increasing the dosage of the drug prescribed or adding a new medicine) will be suggested by doctors when there are critical changes in existing ones (e.g. increased OFFs duration) or newly-detected PD symptoms (e.g. new occurrence of gait impairment). Video recordings After imitating a visual cue on a mobile screen, participants are asked to perform videorecorded UPDRS-III test. Then they are invited to upload the video to the app. Motor



symptoms are judged by clinicians based on the video recording. In addition, an AI automatic method was proposed for studying motor symptoms in PD patients relying on contactless video-based “reading” method. An automatic motor symptoms recognition algorithm was trained to explore the differences of PD movements from the normal movements as well as how to objectively quantify the severity of its motor dysfunctions. Data validation Raw data quality control is the initial step of data analysis for a successful research. In PaWei platform, we take a strategy for assessing the data quality by identifying poorquality data, including incomplete data and illogical data. The completion of data is analyzed through the completion rate of patients’ baseline and regular self-evaluation questionnaires. Besides, 14 pairs of questions, which have exactly similar contents, are purposive selected as “logical testing question”. If the patients’ options are rather inconsistent in these questions (e.g. the patient choose “normal dressing” in UPDRS II scale, while choose “had difficulty with dressing” in PDQ8), the data is identified as “illogical data”. Automated feedback loops are employed with this strategy to enable real-time detection of incomplete data or illogical data, which can be used to improve data collection quality. Data Records Since its inception, a total of 4098 individuals (PD patients and healthy controls) registered and consenting to participate. 109 hospitals across China have joined PaWei platform. Recently, the platform is growing at a rate of approximately 1000 registrants


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per month, clearly demonstrating its usability and acceptability. However, only 40.6% of those who registered were verified by administrator. At baseline, 42.4% of verified participants completed all questionnaires. It might due to strict criteria for identity verification and limitation of compliance. This version of app may have been too challenging or time-consuming to be used for some participants, particularly for elderly individuals or those with cognitive problems even if they receive instructions on how to use app. The next version of app being more user-friendly are being under development. Future directions With more experience and a better understanding on the value of our approach, we expanded the objectives of PaWei platform. It is expected to gradually merge the platform with other data sources, such as gene sequencing data sets and MRI and PET databases. This will promote the build of big database for a variety of research purposes. What’s more, the development of online games to track physical responsiveness and cognition, motor and cognitive rehabilitation programs, and the use of sensors to monitor changes in motor function are covered in the platform’s future plans.

6. Conclusion Based on large clinical datasets, data generated from RWS in PD is helpful to greatly benefit the scientific community and patients and to address issues that are difficult or impossible to study with RCTs. In the past decade, powerful evidence has proved RWS are useful for directing and improving PD intervention strategies such as repurposing



drugs and identifying contraindications. In these RWS, results in line with previous clinical trials give greater confidence in approving the indication; while the discordant results demonstrate the necessary in deeply reexamining the clinical trials. Despite key advantages of RWD already available, limitations in its application should also be kept in mind. A smartphone-based management app can be very valuable in supporting a future effort of RWD collection and optimally taking advantage of the available resources. By minimizing the impacts of confoundings, bias and heterogeneity, it is essential for the ongoing development and application of innovative methods regarding high-quality, comprehensive and valid RWD to provide robust and reliable evidence of RWS in PD.

Conflict of interest The authors declare no conflict of interest.

Author contributions J.W. planned the manuscript. All authors contributed to writing the manuscript. Y.T., K.Y. and J.W. contributed to the revision of the manuscript.

Funding sources This work was supported by the Project (2016YFC1306500) from Ministry of Science and technology of China, the Grants (81771372,81571232,81801260) from the National Science Foundation of China.


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Figure legends

Fig. 1 General hierarchy of study types. In traditional evidence-based medicine, hierarchies have been established to rate the relative strength of evidence of a particular study methodology.

Fig. 2 Schematic representation of PaWei platform cloud-based architecture. The core of the system is a cloud IT system that provides all the necessary functionality for users and services communication, along with compute power for data processing and storage. The platform connects patients, doctors and researchers by establishing communication and data transfer between the cloud platform and the mobile applications over the internet. Real world data collection from PaWei platform allows researchers to provide a rich source of data for RWE studies.

Fig. 3 Mobile application functionality for Patients.


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The primary modules of the PaWei app for patients include self-evaluation, clinic based assessment, medication, Video recordings and other functions.

Fig. 1 General hierarchy of study types.



Fig. 2 Schematic representation of PaWei platform cloud-based architecture.


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Fig. 3 Mobile application functionality for Patients.




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Tables Table 1. Drugs repurposing for Parkinson’s disease in real world studies. Drugs

Approved indications

Database

Statins

Hypercholesterolemia

Health

Participants Professional

Follow-up Study，Nurses' Health Study National

Health

38,192

50,432 patients

National

43,810

Insurance

Research

Results (OR/RR/HR, 95%CI)

Reference

US

Statin users: RR = 0.74; 95% CI, 0.54-1.00; P = 0.049

27

Taiwan

Female statin users: HR 0.65; 95%CI 0.57-0.74

25

90,874 women

Insurance (NHI) database Health

men ，

Country/Region

diabetic

Male statin users: HR 0.60; 95% CI 0.51-0.69 statin

Taiwan

initiators

Continuation

of

lipophilic

statins

users

comparing

with

29

discontinuation: HR=0.42, 95% CI 0.27-0.64

Database US

Veterans

Affairs

database The

394,739

US

Simvastatin users: HR 0.51, CI 0.4-0.55, p < 0.0001

28

US

Statin users: OR= 1.58, P < .0001

30

T2DM

Taiwan

Metformin users: HR=0.40, 95%CI 0.17-0.94

52

Norway

Glitazones users: HR=0.72; 95%CI, 0.55-0.94; P = 0.01

60

Sweden

DPP-4 inhibitor users: OR=0.23; 95% CI 0.07-0.74

50

statin

users MarketScan

Commercial Claims and

21,599 participants

Encounters database Metformin

Type

2

Diabetes

Mellitus Glitazones

Type

2

Diabetes

Mellitus

Taiwan National Health

64,166

Insurance database

patients

Norwegian

94,349 metformin

Prescription

Database

users,

8,396

glitazone users DPP-4 inhibitors

Type Mellitus

2

Diabetes

Swedish Patient Register

980 PD+T2DM 4900T2DM


ACS Chemical Neuroscience 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46

Salbutamol

Bronchospasm,

Norwegian

COPD

Database

Prescription

619,863 users 4,066,119

Page 36 of 39

Norway

OR=0.66 95% CI, 0.58-0.76

61

US

Inosine monophosphate dehydrogenase inhibitors: RR= 0.64; 95%CI

62

non-

users Immunosuppressants calcium

channel

blockers (CCB)

Autoimmune disease Hypertension

United States Medicare

48,295

beneficiaries

52,324 controls

UK-based Practice

General Research

PD

and

3,637 PD

0.51–0.79 Corticosteroids: RR=0.80;95%CI 0.77–0.83 UK

CCB users: OR=0.77;95% CI 0.63-0.95

15

Taiwan

CCB users: HR=0.71;95% CI 0.57-0.90

23

Denmark

CCB users: OR=0.73; 95%CI, 0.54-0.97

16

3,637 controls

Database Taiwan National Health

65,001

Insurance Database

hypertensive patients

Danish

national

hospital/outpatient

1,931 PD patients, 9,651 controls

database


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Table 2. Identifying new contradictions for Parkinson’s disease in real world studies. Drugs

Approved indications

Database

Participants

Beta-blockers

Hypertension,

Norwegian Prescription

4,671,188

arrhythmia

Database

users; 14,794 users

Metformin

Type

2

Diabetes

Mellitus

National

Health

4651

Insurance

(NHI)

users

non-

metformin

Country/Region

Results (OR/RR/HR, 95%CI)

Reference

Norway

Propranolol: OR=2.20 95% CI, 1.62-3.00

61

Taiwan

HR=2.27, 95% CI=1.68-3.07

53

UK

Initiators of antidepressants: RR=1.85, 95%CI, 1.25 to 2.75

56

Taiwan

Co-prescribing rate of APDs:

63

database Antidepressants Antipsychotics

Depression

General

Schizophrenia

Practice

999 PD cases; 6261

Research Database

controls

National

Health

40,561

Insurance

(NHI)

schizophrenia

SGA quetiapine (27.09%), risperidone (66.50); FGA thioridazine

patients

(60.09%), loxapine (96.35%)

database National

Health

Insurance

(NHI)

9830 subjects

Taiwan

flunarizine and cinnarizine users (median observation period 1.5-

64

1.9y) HR=5.117, 95 % CI = 3.758-6.967

database National

Health

44,644

T2DM

Insurance

(NHI)

patients

Health

7877 PD patients

Taiwan

flunarizine exposure period expanded over 3 months: OR=7.03

65

US

mortality risk:

66

database Veterans Administration

olanzapine OR=2.79 95% CI, 1.97-3.96

database

risperidone OR=2.46 95% CI, 1.94-3.12 quetiapine fumarate OR=2.16 95% CI, 1.88-2.48

Metoclopramide

Nausea, Gastroparesis

Migraine,

Longitudinal

Health

Insurance Database

218,931

Taiwan

high-exposure users: HR=3.15, 95% CI: 1.78-5.57

metoclopramide


67

ACS Chemical Neuroscience 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46

Page 38 of 39

users Lithium

Hypnotic

Schizophrenia

Zolpidem

Danish

national

1,293,789

prescription database

participants

National

59,548

adult

patients

newly

Insurance

Health Research

Database (NHIRD)

diagnosed

Denmark

Lithium users: OR=1.88 (95% CI: 1.60-2.20)

68

Taiwan

OR=1.41 95% CI 1.17-1.72

69

with

sleep disturbance


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For Tables of Contents Use Only Evidence of repurposing drugs and identifying contraindications from real world study in Parkinson’s disease Yilin Tang, Ke Yang, Jue Zhao, Xiaoniu Liang, Jian Wang


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