Proximo Discusses: Reading the Tumour

​Reading the tumour: a conversation with two oncology founders

​Cancer medicine has become very good at generating biological data and noticeably less good at knowing what to do with it. A tumour can be sequenced in days. Working out which of the thousands of resulting signals actually explains why this particular cancer is growing — and which drug would stop it — remains slow, expensive and concentrated in a handful of academic centres.

​We're hosting two founders attacking that gap from opposite ends.

​The first works upstream, growing patients' own tumour tissue outside the body in a way that preserves the surrounding microenvironment — the immune and structural cells that simpler lab models strip away — then using computer vision to watch how those living samples respond. The bet is that a more faithful model produces findings that survive contact with real patients.

​The second works downstream, at the point where a patient already has a diagnosis and a molecular profile. Their platform reads DNA, RNA and protein together to identify which pathways are actively driving a tumour, then puts a ranked set of treatment options in front of a senior oncologist to review and sign off.

​Expect a working conversation rather than a pitch: what breaks when you move biology from the bench into a clinical workflow, why interpretation is harder than measurement, and what it takes to build in a field where being wrong is expensive.

​Come with questions!