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Robust combination testing: Methods and application to Covid-19 detection
Sanjay Jain1, Jonas Jonasson2, Jean Pauphilet3, Kamalini Ramdas3
1Department of Economics, University of Oxford; 2MIT Sloan School of Management; 3London Business School
For COVID-19 detection, point-of-care tests are cheap and quick but fail policymakers’ accuracy requirements. We propose a robust optimization methodology for optimally combining results from cheap tests for increased diagnostic accuracy. Combining three rapid tests increases area under the curve by 6% compared with the best performing individual test for antigen detection. We demonstrate that robust optimization is a powerful tool to avoid overfitting and improve out-of-sample performance.
Adaptive approval of drugs for rare diseases
Wendy Olsder1, Tugce Martagan1, Jan Fransoo2, Carla Hollak3
1Eindhoven University of Technology, School of Industrial Engineering, Eindhoven, The Netherlands; 2Tilburg University, Tilburg School of Economics and Management, Tilburg, The Netherlands; 3Department of Endocrinology and Metabolism, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
Adaptive approval is a novel regulatory program that enables earlier patient access to new drugs for rare diseases. The program has been in place for almost a decade, however, industry participation has been surprisingly low. We present a Stackelberg game-theoretic model to understand why industry participation has been low. Our results inform healthcare policymakers on ways to redesign adaptive approval programs to likely increase industry participation and improve patients' welfare.