Overreliance on Cost Reduction as a Featured Element of Sensor

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Perspective

Overreliance on Cost Reduction as a Featured Element of Sensor Design Daniel J Wilson, Ashok A. Kumar, and Charles R. Mace ACS Sens., Just Accepted Manuscript • DOI: 10.1021/acssensors.9b00260 • Publication Date (Web): 22 Apr 2019 Downloaded from http://pubs.acs.org on April 23, 2019

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Overreliance on Cost Reduction as a Featured Element of Sensor Design

Daniel J. Wilson,1 Ashok A. Kumar,2 and Charles R. Mace1*

1Department

of Chemistry, Tufts University, 62 Talbot Avenue, Medford, MA 02155 2Jana

Care, 8 St. Mary’s St. #611, Boston, MA 02215

*Corresponding author: [email protected]

Keywords: low cost, commercialization, manufacturing, point-of-care, diagnostics, lateral flow, paper-based microfluidic devices

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Abstract In this perspective, we examine the role of cost in sensor design, its meaning within the context of converting academic prototypes into commercial products, and the importance of these issues to clear scientific communication. The possible motivations to consider the cost of a technology, sensor, or assay are both numerous and apparent. However, the idea that the cost of reagents and materials at the laboratory scale will directly translate to the purchase price for a user is inaccurate. While calculating the bill of materials is easy, there are many business considerations that make commercial products entirely different from academic prototypes. With these critical aspects of commercialization considered, academics are often not equipped to predict what the final price of an assay, sensor, or instrument will be to the end user. When used without proper context and accuracy, an overreliance on the phrase “low cost” in the absence of a sufficient discussion of cost weakens the meaning of this popular term and precludes practical scientific advancements. To demonstrate how the relationship between a bill of materials and “expected purchase price” breaks down when considering academic innovations, we discuss pregnancy tests as a case study where an academic bill of materials can lead to both overestimations and underestimations of pricing.

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In current literature, emphasis on perceived reduction of device fabrication costs has emerged as a required component of sensor design, with readers and reviewers expecting sensors to be described as “low cost” without appropriate context for critical cost considerations of a demonstrated sensor. This use of “low cost” can lead to two problems: (i) over-estimation of production costs—due to miscalculation of manufacturing efficiencies and material costs at scale—can lead to a technology being overlooked or under-funded, and (ii) under-estimation of production costs—due to a lack of accounting for packaging, factory overhead, labor, etc.—can lead to inappropriate comparisons of technologies. In this perspective, we aim to demonstrate that device cost estimates for academic prototypes are of limited utility and that use of the phrase “low cost” in the literature does not necessarily indicate feasibility of prototypes as products. Manufacturing cost is a driving factor in delivering affordable diagnostic technologies, as all potential users do not have sufficient funds to purchase devices and assay kits,

1, 2, 3

and the

purchase price of a sensor is dependent on its target application and market. Instruments in well-equipped laboratories are often purchased for a negotiated competitive price, which is not usually considered a barrier to acquisition.4 However, smaller practices with less negotiating power are more sensitive to the sticker price of equipment and recurring consumables and may opt for technologies with lower capital costs that are designed for point-of-care use.5 Requirements for clinical measurements in remote or impoverished settings present unique and difficult challenges that have led to the development of innovative devices.6,

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In centralized

laboratories or at the point-of-care, the final price of a technology must not present a barrier to purchase or access to healthcare, but also allow a manufacturer to recover production costs and make profits.

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Practical considerations for “low cost” as a goal of sensor design Because accessibility is required for adoption of point-of-care technologies, cost has long been an important criterion for the development of sensors.8, 9, 10 In 2006, the WHO helped to establish the ASSURED criteria11 to create design guidelines for developers of diagnostic devices for sexually transmitted infections. Many have, rightly or wrongly, applied these general rules to all point-of-care tests designed for low-resource settings. These criteria are used to determine whether tests meet disease control needs: Affordable, Sensitive, Specific, Userfriendly, Rapid and robust, Equipment-free, and Deliverable to end-users. These guidelines were established to drive the creation of deliverable diagnostic tests, but, more than a decade after their introduction, focus on the element of device affordability has shifted from its original intention. Some of these criteria, such as sensitivity and specificity, can be described quantitatively by comparing the results from a prototype sensor to standard clinical assays. Other evaluations, such as user-friendliness or rapidity, can be compared qualitatively to standard protocols with consideration that these point-of-care tests are being performed in non-laboratory settings by users with minimal formal training. These assessments require recognition of potential benefits that non-standard analytical methods may provide to target users of these devices. Additionally, expectations must evolve over time to reflect advancements in sensing technologies. The “equipment free” criterion was intended to offer alternatives to bulky and expensive instrumentation that precluded deliverability. A modern interpretation accepts the ubiquity of electronic readers (e.g., personal glucometers), and has expanded to include smartphones and accessory tools12 to enable quantitative measurements and network-based disease management strategies. While most elements of the ASSURED acronym have grown with the field and can still be used to evaluate the potential of a point-of-care sensing technology, current discussions of

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device affordability have not followed this trend. Common practices of (i) treating a fabrication cost estimate at the academic laboratory scale as a final purchase price or (ii) describing a device as “low cost” without providing any manufacturing details are inappropriate. In this perspective, we use detailed definitions (Box 1) to describe the highly variable components that comprise a commercial product’s purchase price in support of this claim. Additionally, we present results of a detailed literature analysis and case study to suggest that providing relevant context for a proposed sensor’s feasibility as a cost-effective technology holds more value for the academic sensors community than inaccurate or unjustified claims of “low cost.”

Box 1. Definitions: Bill of Materials (BOM): A list of materials, parts, and associated quantities and costs required for manufacturing an end product. These costs only account for the raw components of the assembled device but exclude remaining manufacturing requirements. Cost of Goods Sold (COGS): Direct costs attributed to manufacturing products sold by a company. This amount includes the bill of materials, labor, and, in some cases, factory operating expenses related to production. A COGS generally excludes company spending unrelated to production, including business operations, marketing, and capital expenses. Operating Expenses (OpEx): Expenses incurred through business operations (e.g., rent, marketing, payroll, insurance) that must be efficiently managed for a company to make profits. Capital Expenses (CapEx): Costs attributed to tangible (e.g., real estate, equipment) and intangible (e.g., intellectual property, licensing) investments required for competition and growth. Price: The combined significance of COGS, OpEx, CapEx, and requirements for profit are reflected by a final dollar amount paid by a user to purchase a sensing technology.

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There are several reasons why it is inappropriate for academic researchers to estimate the purchase price of a translated prototype. Most academic cost evaluations are bills of materials (BOM), in which costs reflect institution-dependent pricing agreements. Packaging materials such as vials, foil pouches, and desiccants are often overlooked in BOM calculations, but are critical components when devices require dry chemical storage. Additionally, an academic BOM does not account for labor performed by students or trainees, such as converting materials or assembling and packaging components. This figure also excludes startup costs and overhead required for operating a facility with quality control systems and dedicated equipment (e.g., microfabrication tools) or specialized areas (e.g., dry rooms, clean rooms). In industry, these values are accounted for in the cost of goods sold (COGS), a figure that captures the cost of labor and plant overhead in addition to material costs. The COGS is typically not tabulated for academic prototypes because it is difficult to accurately estimate the costs of researcher labor. Companies must also account for operating expenses (OpEx) that are required to run a business (e.g., marketing, technical support, and regulatory compliance) and capital expenses (CapEx) required for efficiency, competition, growth, and making profits. These factors highlight critical differences between the structure of academic research groups and emerging or established companies (Figure 1), which make it difficult for academics to estimate the conversion costs or purchase prices of commercial products. Although the sum of material costs is not explicitly equated to purchase price in academic journals, this value is often regarded as such by readers, resulting in direct comparison of prototyping costs to laboratory test fees or instrument prices. For example, any sensor incorporating an antibody may be deemed “expensive” due to their high costs when sourced at the academic scale (ca. hundreds of dollars per mg). Because it is impossible to know the final purchase price of an academic prototype without establishing a real company, this improper juxtaposition can significantly detract from the translational potential of new sensors and devices. 5


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Use of the phrase “low cost” in scientific literature and communication Perceptions framed by these evaluations of device potential have encouraged authors to loosely describe prototypes as “low cost” without providing acceptable supporting evidence. We performed a detailed literature analysis of all papers published in ACS Sensors since its launch in 2016 and all papers published in Analytical Chemistry in 2018 to determine how frequently descriptions of “low cost” technologies are actually supported by details of manufacturing costs. Our search returned 672 publications. We excluded 158 papers that were not relevant, including non-experimental publications (e.g., reviews, perspectives, editorials) and other papers that met detailed exclusion criteria described in the Supporting Information. We analyzed remaining publications by searching for currency symbols or abbreviations (e.g., $, €, USD, RMB), “cost”, and related terms (e.g., cheap, affordable, expensive, inexpensive, price). From our search results, we determined whether authors provided (A) a full bill of materials, (B) a sum of material costs, (C) a cost comparison to relevant technologies, (D) specific costs of only some (i.e., one or more, but not all) components of a device, or (E) did not sufficiently describe approaches where “low cost” was listed as an advantage. Our results (Figure 2) show that fewer than 9% of evaluated papers provide an appropriate discussion of important cost considerations. Among the papers that support use of “low cost” as a beneficial feature of sensors and devices, papers that provide a BOM (A) are the most informative example of academic cost estimates. This approach, demonstrated by Ainla et al.,13 details the source, catalog information, and purchase prices for specified volumes of raw material that comprise a finished prototype. These details enable verification of pricing information and streamline replication of described sensors. Summaries of material costs (B), demonstrated by Tang et al.,14 provide the reader with an idea of barriers to entry for performing a given measurement but lack the benefits of transparency afforded by a BOM. Similarly, cost comparisons (C) can demonstrate potential advantages of a new approach over existing standards but provide limited insight into sensor

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manufacturability.15 Finally, incomplete cost descriptions (D) are typically not instructive, but can be useful in certain scenarios (e.g., inexpensive, versatile, or accessible reagents).16 In our literature analysis, the vast majority of publications used “low cost” or equivalent terms to justify decisions related to experimental design—whether measurement approach, reagent use, or instrument selection—without providing appropriate context for why “low cost” was a motivation during the sensor design process or an advantage of the completed prototype.

Case study: diagnostic devices for pregnancy testing To underscore our concerns with this trend, we need to quantify two factors: (i) how costs can change with scale, even at the academic level, and (ii) how costs cannot be tied directly to the final purchase price of a commercial product. As a result, we completed a detailed bill of materials analysis (Supporting Information) for a paper-based microfluidic device that our lab has previously demonstrated using an immunoassay for hCG (i.e., a pregnancy test).17,18 This specific device and assay facilitates a useful, direct comparison of prototype material costs to prices of commercial lateral flow pregnancy tests. At the academic prototyping scale, meaning the volumes of material and reagents we would purchase to fabricate devices for publication, the total material cost per device is $0.75. At the largest scale for which we can calculate a BOM, meaning the largest volumes of material we can purchase through our institutional vendor agreements, the total material cost is $0.22 per device (Table 1). The difference between scales can be attributed to the costs of Nylon capture membrane and antibodies. There is approximately a 5-fold difference in membrane cost and a 2-fold difference in reagent cost between scales. Otherwise, costs of remaining components remain about the same. These estimates are strikingly different from purchase prices of commercial pregnancy tests. In the US, basic pregnancy tests (i.e., those that rely on the user to interpret a positive result without the help of an electronic interface) retail for approximately $4 per test, so a BOM of

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$0.22 may seem appropriate. However, in price-sensitive markets like India, pregnancy tests retail for as low as 20 rupees per test (ca. $0.28), suggesting that the total material cost must be much lower than $0.22. Indeed, wholesalers on Alibaba.com sell pregnancy test strips for as low as $0.03 per test. Tests of different volume, history, or demand may be significantly more expensive, even if using the same lateral flow format. For example, Sickle SCAN, a point-ofcare lateral flow test for sickle cell disease is currently sold for $5–$10,19 likely due to the specialized antibodies and complex test design required to differentiate between hemoglobin variants.

Key differences between academic prototypes and commercial products The difficulties of estimating purchase prices stem from key differences between academic research laboratories and established companies. Singular academic prototypes allow universities to produce and license intellectual property, but the overall focus of these institutions is not commercialization of emerging technologies. On the other hand, companies exist to generate profit by driving large volumes of new technology into the mainstream. As a result, available resources and strategic decisions are completely different for developing academic prototypes and commercial products. Recognizing the vast number of sensor types and prototyping strategies, we will use this perspective to focus on a single field, paper-based microfluidics, due to its intimate relationship with the ASSURED criteria and the concept of low costs. One characteristic example of the differences between academia and industry is the consideration of scale for material acquisition and prototype manufacturing. Academic research groups typically purchase small amounts of raw material (e.g., paper and reagents) for prototype fabrication, while companies require large volumes of goods for production-scale manufacturing of validated lots of sensors. Unit prices scale with quantity, meaning that identical devices made in academia and industry have dramatically different material costs. In academia, 8


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devices are fabricated in small batches at the bench18 by protocols optimized for device performance but not manufacturing efficiency. In industry, however, devices may be manufactured by manual or automatic (e.g., roll-to-roll systems for lateral flow tests)20 processes optimized for speed and leanness to maximize profit. Because manufacturing strategies are selected based on scale and constraints imposed by expenses, the hypothetical COGS for a commercial device is highly variable and difficult to estimate. This uncertainty may explain why the BOM has become a preferred metric in academic literature, but it is still not an accurate estimation of commercial material costs. Academics typically focus on reducing device production costs by using inexpensive materials that are compatible with simple manufacturing protocols, but the final cost of preparing a device for distribution encompasses far more than production considerations. Companies must allocate funds to ensure that their devices meet specific manufacturing standards (e.g., ISO 13485:2016, 21 CFR 820)21,

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required for certification by regulatory bodies (e.g., FDA

approval, CE mark). Similarly, academics generate intellectual property without ever having to bear filing costs, while companies can pay massive licensing fees to develop a single product. There are too many unknown factors for academics to reasonably estimate the final purchase price of a product. Instead, academics should focus on providing a context for experimental decisions or advantages related to cost, including an accurate bill of materials where possible, and recognize that discussions of manufacturing context or compatibility with existing production strategies provide greater evidence for commercial feasibility than misguided attempts at estimating scaled production costs or purchase prices.23

Guidelines for describing and interpreting academic sensor prototypes Current standards, requiring no evidence or justification for calling a sensor “low cost,” have deflated the meaning of this appealing phrase, making it difficult for readers to discern practical

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devices with real-world utility from incremental or misconceived demonstrations described by a popular keyword. To ensure that this label is used responsibly, those seeking to publish in academic journals must provide important details based on the context of how a prototype is manufactured, used, and required to perform. While there are a handful of informative approaches to objectively describe a prototype, providing no context or explanation for using “low cost” is not acceptable. A bill of materials is the most detailed means of demonstrating that a sensor is “low cost,” especially when other point-of-use or cost-effective devices, not just capital equipment, are competing technologies. However, a standalone sum of prototype material costs can also be very informative, especially when compared to the cost of a standard approach. These comparisons can be compelling when a proposed method costs orders of magnitude less than the reference method, but should be supported with cost estimates,24 where possible, to highlight potential savings. Incomplete cost information (e.g., costs of individual reagents or components) is not sufficient to call an entire approach “low cost,” but can inform sensible device design strategies. While each of these strategies may be appropriate to describe a particular sensor’s potential cost-effectiveness, it is inappropriate to describe a device as “low cost” without diligent evaluation of device-specific cost considerations. Additionally, readers must be appropriately critical of devices described as “low cost” in the literature, while understanding that final prices are exceedingly difficult for academics to estimate. Detailed cost assessments do not include startup manufacturing expenses, which could be substantial upon scaling for production. For example, equipment for fabricating paperbased microfluidic device prototypes (e.g., printer, scissors, adhesive) are less expensive than the environment and equipment necessary for fabricating traditional microfluidic devices (e.g., cleanroom, plasma systems). However, transitioning to high volume manufacturing methods (e.g., roll-to-roll systems vs. injection molding) will have completely separate costs embodied by capital and operating expense figures and other concerns related to establishing a final price. Ultimately, audiences must expect justification for labeling a device as “low cost,” but also be 10


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able to look beyond material costs to consider the context of a sensor’s purpose, manufacturability, and target user base to determine its utility as a potentially cost-effective solution.

Conclusions Manufacturing

costs

and

consumer

purchase

prices

are

complicated

financial

considerations that are beyond the scope of academic prototype development. It is critical that academics continue to develop sensors and technologies with affordability, and ultimately accessibility, as key elements of the design process, but also recognize their limitations in assessing the translational potential of prototype devices. The phrase “low cost” may be used to describe these prototypes, but only when supported appropriate context surrounding manufacturing costs and protocols. This of lack of precision use of language is not limited to “low cost” (e.g., ultrasensitive sensors)25 and highlights a broader issue in the objective description of prototypes and methods. Academic material costs should not be used as a rigid figure for planning commercial manufacturing, but as a suggestion that a technology could potentially become an affordable, practical product. Accordingly, interpretation of “low cost” in publications requires careful consideration of sensor materials, fabrication methods, and comparison to standard approaches. Moving forward, rethinking the way that we, as academic scientists and inventors, describe and consider prototype sensors will appropriately refocus conversation away from flawed projections of future results or applications and toward objective evaluations of performance and feasibility.

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Acknowledgements This work was supported by Tufts University and by a generous gift from Dr. James Kanagy.

Supporting Information Results of detailed literature search; Tables S1–S3. Detailed calculations for low volume and high volume manufacturing material cost estimates; Figure S1; Tables S4–S12.

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Figure 1. Flowchart depicting important financial considerations that contribute to the final purchase price of a commercial product. Only one of which, the bill of materials, is typically estimated during the development of academic prototypes.

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Figure 2. Pie chart depicting classification of publications that use the phrase “low cost” to describe a sensor or technology. Papers that provide a complete bill of materials (A) are shown in red, while papers that provide a sum of raw material costs required for prototype fabrication (B) are depicted in green. Papers that compare the cost of the described approach to that of an existing method (C) are shown in yellow, and papers that provide incomplete cost analyses (i.e., one or more components, but not all components, (D) are depicted in purple. Finally, manuscripts that do not provide sufficient justification for the use of the phrase “low cost” (E) are shown in blue. These data are based on a detailed literature analysis of 514 peer-reviewed manuscripts published in ACS Sensors (ca., 2016–2018) and Analytical Chemistry (ca., 2018 only).

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Table 1. Comparison of bill of materials (BOM) totals for academic prototypes of home pregnancy tests at two material purchasing scales to prices of consumer products in different international markets.

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TOC Figure

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