What clinical research keeps getting wrong about patients
Clinical research turns patients into numbers, and a former medical device engineer says that is exactly where it fails. Niharika Singh, a pre-medical student who led device projects at Genentech, Abbott, and AstraZeneca, argues that counting patients is not the same as engaging them. The data tells you what happened. It almost never tells you why. This is a conversation about the human signal that protocols, machines, and AI keep missing, and what physicians lose when they stop asking. ⏱️ Chapters: 0:00 Introduction 0:34 From medical devices to medical school 1:50 Why surgery ignores the patient voice 3:21 The difference between counting a patient and engaging one 6:00 The hernia trial that changed in Ghana but not India 7:45 The question no one asks about your real numbers 9:57 The questions that pull out the truth a chart cannot 12:32 Why AI makes the human connection matter more 14:37 What device validation taught her about patients 19:45 Take home messages About this episode: Niharika Singh trained as a biomedical engineer and led medical device research at companies like Genentech, Abbott, and AstraZeneca before pivoting toward medical school, and she brings that outsider vantage point to a sharp critique of clinical research. She argues that most studies reduce patients to a single data point, capturing the numbers while losing the qualitative truth of why a treatment works or fails for a given person. Drawing on her device background, she maps the discipline of design verification and validation onto surgical research, making the case that patient engagement is a form of clinical validation that researchers routinely skip. She walks through a United Nations SurgHub case study, the Tiger hernia trial run in India and Ghana, to show how involving policymakers, hospitals, and local patients reshaped what care was even legally possible in each country. She presses on the hard objection that resource-constrained researchers lack the bandwidth for this deeper engagement, and frames the rise of AI in medicine as the very reason clinicians must protect the human connection rather than surrender it. Along the way she draws on her work as a consciousness educator and on books like The Elusive Body to argue that understanding yourself is a prerequisite for understanding a patient. Her closing messages center on surgical care, originality in an age of machines, and refusing to let the data flatten the person in front of you. It is an unusual, wide-ranging conversation that moves from regulatory science to emotional intelligence in a single arc. 🤝 Partner with me on the KevinMD platform: With over three million monthly readers and half a million social media followers, I give you direct access to the doctors and patients who matter most. Let's work together to tell your story. ➡️ PARTNER WITH KEVINMD: https://kevinmd.com/influencer ➡️ SUBSCRIBE TO THE PODCAST: https://www.kevinmd.com/podcast ➡️ RECOMMENDED BY KEVINMD: https://www.kevinmd.com/recommended #ClinicalResearch #PatientEngagement #SurgicalCare

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