Insights on AI, medical research, and the future of scientific discovery.
The p-value is the most widely misunderstood statistic in science. Understanding what it actually means changes how you read the literature, design your studies, and report your findings.
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You have read everything relevant. Translating that into a specific, novel, testable hypothesis is where the real difficulty starts.
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Evidence-based medicine transformed clinical practice. It also produced a hierarchy of evidence that has been applied with a rigidity its founders would not have recognised or endorsed.
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The paper that challenges your hypothesis might be in a database you never thought to search. Searching 12 databases simultaneously changes what you find.
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AI-designed molecules have entered clinical trials. AI-predicted protein structures have transformed structural biology. But the evidence for AI's impact on drug discovery success rates is more complicated than the headlines suggest.
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Why we built NousLab, and what we believe researchers actually need.
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Reading papers is not the same as extracting usable data from them. Most literature reviews produce summaries when they should produce structured datasets.
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Most clinical trial failures are not failures of execution. They are failures of design that were locked in before the first patient was enrolled.
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Most teams use AI to find papers faster. That is the least interesting thing it can do. Here is what changes when you treat it as a research infrastructure.
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Every researcher learns about bias in methods training. Most learn a list of names. What is harder to teach is how to recognise them in your own work before peer review does it for you.
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A rapid review done poorly is worse than no review at all. It gives false confidence in conclusions drawn from incomplete evidence. Here is how to do it properly.
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Real-world evidence is being used to support regulatory decisions in ways that would have been unthinkable a decade ago. That is either exciting or alarming, depending on how well you understand its limits.
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