Biomedical Diagnostics Enabled by Integrated Organic and Printed Electronics.

Organic and printed electronics integration has the potential to revolutionize many technologies, including biomedical diagnostics. This work demonstrates the successful integration of multiple printed electronic functionalities into a single device capable of the measurement of hydrogen peroxide and total cholesterol. The single-use device employed printed electrochemical sensors for hydrogen peroxide electroreduction integrated with printed electrochromic display and battery. The system was driven by a conventional electronic circuit designed to illustrate the complete integration of silicon integrated circuits via pick and place or using organic electronic circuits. The device was capable of measuring 8 µL samples of both hydrogen peroxide (0-5 mM, 2.72 × 10-6 A·mM-1) and total cholesterol in serum from 0 to 9 mM (1.34 × 10-8 A·mM-1, r2 = 0.99, RSD < 10%, n = 3), and the result was output on a semiquantitative linear bar display. The device could operate for 10 min via a printed battery, and display the result for many hours or days. A mobile phone "app" was also capable of reading the test result and transmitting this to a remote health care provider. Such a technology could allow improved management of conditions such as hypercholesterolemia.

Inappropriate Laboratory Testing: Significant Waste Quantified by a Large-Scale Year-Long Study of Medicare and Commercial Payer Reimbursement.

CONTEXT.­: Laboratory testing, beyond what is essential for managing health, is considered low-value care, posing patient risks and wasting resources. Measuring excess testing on a national level is crucial to identify waste and optimize healthcare resource allocation for maximum impact. OBJECTIVE.­: To measure inappropriate laboratory testing and its cost across Medicare and many US commercial payers. DESIGN.­: A retrospective analysis on 2019 claims data measured the frequency of 4 commonly used laboratory tests among 64 million individuals with Medicare and 168 million with commercial insurance. Tests included 25-hydroxy vitamin D, prostate-specific antigen, lipid panel, and hemoglobin A1c. Clinical guidelines, medical literature, and payer recommendations were used to determine appropriate testing frequencies. Costs of excessive testing were calculated using the 2019 clinical lab fee schedule. A targeted analysis of 2022 data confirmed 2019 trends. RESULTS.­: Analysis of ∼84 million tests from ∼1 billion outpatient test claim records revealed that 7% to 51% of tests exceeded recommended frequencies, with some egregious overuse: for example hemoglobin-A1c or prostate-specific antigen every week. The conservative cost estimate for 4 excess tests surpassed $350 million. CONCLUSIONS.­: This extensive study, involving 232 million people, found that 14.4 million of 60.5 million individuals (23.8%) tested had undergone excessive laboratory testing, with likely little benefit and possible harm. Extrapolating findings to all laboratory testing suggests that Medicare alone may have incurred direct excess expenses from $1.95 to $3.28 billion in 2019, without factoring the hidden costs of excessive testing (eg, downstream care). Addressing unnecessary testing is crucial to lowering costs and redirecting resources for greater patient benefit.

Delivering the precision oncology paradigm: reduced R&D costs and greater return on investment through a companion diagnostic informed precision oncology medicines approach.

BACKGROUND: Precision oncology medicines represent a paradigm shift compared to non-precision oncology medicines in cancer therapy, in some situations delivering more clinical benefit, and potentially lowering healthcare costs. We determined whether employing a companion diagnostic (CDx) approach during oncology medicines development delivers effective therapies that are within the cost constraints of current health systems. R&D costs of developing a medicine are subject to debate, with average estimates ranging from $765 million (m) to $4.6 billion (b). Our aim was to determine whether precision oncology medicines are cheaper to bring from R&D to market; a secondary goal was to determine whether precision oncology medicines have a greater return on investment (ROI). METHOD: Data on oncology medicines approved between 1997 and 2020 by the US Food and Drug Administration (FDA) were analysed from the Securities and Exchange Commission (SEC) filings. Data were compiled from 10-K, 10-Q, and 20-F financial performance filings on medicines' development costs through their R&D lifetime. Clinical trial data were split into clinical trial phases 1-3 and probability of success (POS) of trials was calculated, along with preclinical costs. Cost-of-capital (CoC) approach was applied and, if appropriate, a tax rebate was subtracted from the total. RESULTS: Data on 42 precision and 29 non-precision oncology medicines from 56 companies listed by the National Cancer Institute which had complete data available were analysed. Estimated mean cost to deliver a new oncology medicine was $4.4b (95% CI, $3.6-5.2b). Costs to bring a precision oncology medicine to market were $1.1b less ($3.5b; 95% CI, $2.7-4.5b) compared to non-precision oncology medicines ($4.6b; 95% CI, $3.5-6.1b). The key driver of costs was POS of clinical trials, accounting for a difference of $591.3 m. Additional data analysis illustrated that there was a 27% increase in return on investment (ROI) of precision oncology medicines over non-precision oncology medicines. CONCLUSION: Our results provide an accurate estimate of the R&D spend required to bring an oncology medicine to market. Deployment of a CDx at the earliest stage substantially lowers the cost associated with oncology medicines development, potentially making them available to more patients, while staying within the cost constraints of cancer health systems.

Cost-effectiveness of precision diagnostic testing for precision medicine approaches against non-small-cell lung cancer: A systematic review.

Precision diagnostic testing (PDT) employs appropriate biomarkers to identify cancer patients that may optimally respond to precision medicine (PM) approaches, such as treatments with targeted agents and immuno-oncology drugs. To date, there are no published systematic appraisals evaluating the cost-effectiveness of PDT in non-small-cell lung cancer (NSCLC). To address this gap, we conducted Preferred Reporting Items for Systematic Reviews and Meta-Analyses searches for the years 2009-2019. Consolidated Health Economic Evaluation Reporting Standards were employed to screen, assess and extract data. Employing base costs, life years gained or quality-adjusted life years, as well as willingness-to-pay (WTP) threshold for each country, net monetary benefit was calculated to determine cost-effectiveness of each intervention. Thirty-seven studies (50%) were included for analysis; a further 37 (50%) were excluded, having failed population-, intervention-, comparator-, outcomes- and study-design criteria. Within the 37 studies included, we defined 64 scenarios. Eleven scenarios compared PDT-guided PM with non-guided therapy [epidermal growth factor receptor (EGFR), n = 5; programmed death-ligand 1 (PD-L1), n = 6]. Twenty-eight scenarios compared PDT-guided PM with chemotherapy alone (anaplastic lymphoma kinase, n = 3; EGFR, n = 17; PD-L1, n = 8). Twenty-five scenarios compared PDT-guided PM with chemotherapy alone, while varying the PDT approach. Thirty-four scenarios (53%) were cost-effective, 28 (44%) were not cost-effective, and two were marginal, dependent on their country's WTP threshold. When PDT-guided therapy was compared with a therapy-for-all patients approach, all scenarios (100%) proved cost-effective. Seven of 37 studies had been structured appropriately to assess PDT-PM cost-effectiveness. Within these seven studies, all evaluated scenarios were cost-effective. However, 81% of studies had been poorly designed. Our systematic analysis implies that more robust health economic evaluation could help identify additional approaches towards PDT cost-effectiveness, underpinning value-based care and enhanced outcomes for patients with NSCLC.

Driving personalized medicine: capturing maximum net present value and optimal return on investment.

In order for personalized medicine to meet its potential future promise, a closer focus on the work being carried out today and the foundation it will provide for that future is imperative. While big picture perspectives of this still nascent shift in the drug-development process are important, it is more important that today's work on the first wave of targeted therapies is used to build specific benchmarking and financial models against which further such therapies may be more effectively developed. Today's drug-development teams need a robust tool to identify the exact drivers that will ensure the successful launch and rapid adoption of targeted therapies, and financial metrics to determine the appropriate resource levels to power those drivers. This special report will describe one such benchmarking and financial model that is specifically designed for the personalized medicine field and will explain how the use of this or similar models can help to capture the maximum net present value of targeted therapies and help to realize optimal return on investment.