Turns a tumour gene report into the options a patient can actually get in India
TL;DR Regimenly takes the tumour sequencing report an oncologist already has and adds an India-specific layer - which suggested drugs are approved here, roughly what they cost, which assistance schemes exist, and which registered Indian trials are recruiting. Hospitals and testing labs pay. It sells clarity on access, not a better treatment choice.
India had an estimated 14.6 lakh new cancer cases in 2022, with about 15.7 lakh projected for 2025[1]. More of these patients now get next-generation sequencing (NGS) reports, but the reports are all over the place. In a survey of 58 Indian oncologists, 71% said reporting varies from lab to lab and 72% did not know the reporting guidelines[2].
The sharper finding is this one - about 40% said they felt helpless when a report pointed to a therapy they could not get in India[2]. A report written for a US formulary leaves the doctor to do the access research alone, usually squeezed in between other patients.
What it does, in regulatory terms: information and access support for the treating oncologist, not diagnosis or treatment selection. Software that recommends therapy can count as a medical device under the Medical Devices Rules 2017, which explicitly cover software[3], so Regimenly must not rank treatments. Get a regulatory opinion before launch.
The oncologist or lab uploads the NGS report. Regimenly reads each actionable finding and builds a one-page access sheet covering whether the matched drug has Indian approval, typical price bands, manufacturer assistance programmes, and recruiting trials on the Clinical Trials Registry-India, where registration has been mandatory since 2009[4]. A pharmacist-curator checks every sheet before release, and AI only does the first-pass extraction.
The seed wanted to simulate each patient's pathways to pick the best drug, and I reframed it. Pathway simulation is unproven at the bedside, and an Indian precision-oncology firm already sells a patient-twin decision tool in India[5]. The unmet need the survey shows is access, not prediction.
The patient benefits, but hospitals and NGS labs pay. A lab that bundles an India access sheet makes its report easier to act on than a rival's. Cancer hospitals running molecular tumour boards are the second buyer. I found no public price list for Indian NGS tests or report add-ons, so you'll have to discover the per-report fee in pilots.
Indian oncologists have now put the gap in writing. The 2023 survey found 98% wanted uniform NGS reporting and 93% an Indian data repository[2]. CTRI lists over 1.2 lakh registered trials[4], enough to make trial matching useful, and language models have made reading messy report PDFs cheap.
There's no public figure for Indian NGS report volumes or spend on report interpretation. The firmest signals are the 14.6 lakh annual cancer cases[1] and the 40% of surveyed oncologists who struggle when a recommended drug is unavailable[2]. Treat the case count as a ceiling, since only a fraction of patients get sequenced.
One precision-oncology firm runs tissue and liquid profiling plus a patient-twin tool that supports molecular tumour boards[5]. Another tool, built with Tata Memorial's ACTREC, automates NGS interpretation[6]. Both start from the biology.
From what's published, none of them makes an India-specific access sheet that sits on top of any lab's report. That neutral, lab-agnostic layer is the gap.
| Difficulty | Moderate (44/100) |
| Starting capital | ₹60 L–1.1 Cr |
| Time to launch | 6–9 months |
The software is modest. The hard part is keeping drug approval, price and trial data current every single week, and that takes a pharmacist and an oncology adviser, not just code. Labs also guard their report format, so the first deal needs a lab willing to co-brand.
This is regulated territory. Software that recommends therapy can count as a medical device, so how you scope the product decides which rules apply.
Building this outside India? The categories above usually have a local equivalent, so check with your own regulator.
This product supports access, not treatment choice. AI must never rank drugs or suggest a therapy, and a human curator signs off every sheet before an oncologist sees it.
Want to work out the AI layer for Regimenly? Talk to Yash →
I like this for a founder with oncology pharmacy or medical affairs experience who genuinely enjoys careful, repetitive curation. If you're set on building a clever AI model then this will bore you. First prove that one lab will pay per report and that oncologists open the sheet in at least half of cases.
Plan for roughly ₹60 L–1.1 Cr, mostly on the curation team, the drug and trial database and a regulatory opinion.
It depends on what it does. Software that recommends treatment can be a medical device under the Medical Devices Rules 2017, so keep it to information and access, and get a written opinion.
Yes, but the access layer is local by nature. You'd rebuild the approval, price, assistance and trial data for that country and check how its regulator treats clinical software.
The free Regimenly validation kit has the line-by-line capital breakdown, the effort scoring, the medical-software and data-protection checklist, a 14-day validation sprint with pass/fail targets, a 90-day launch plan, 10 interview questions for oncologists and labs, and 5 assumptions to test. Download the kit →
Thinking about building Regimenly or something close to it? The make-or-break bit is staying on the right side of the medical-software line while still being useful to the oncologist, and I'm happy to help you draw that line. If you need a hand, you know where to find me. Talk to Yash →
For illustration only. Names are fictional and ideas hypothetical; sourced facts are real but may be out of date. Nothing here is legal, financial or professional advice, and Yash Khatri is not personally liable for any use of it. Read the full disclaimer.