The Science of Better Health

Find it. Prove it. Deliver it : 3 hurdles every medicine must clear before it reaches a patient, told by the founders tackling each one.

Opening Note

Every drug makes the same journey. It must be found, proven to work in the human body, and delivered at the right dose and in the right condition to the person who needs it. That journey is what we mean by the science of better health, and at every stage, something gets lost.

The losses are stark. Nearly 90% of protein targets in the human body still have no known drug candidate. Of the candidates that clear animal studies, roughly nine in ten fail in humans. And vaccines which we have had for decades, has still failed to reach 14.3 million children in 2024. So this edition asks one question: why do so many breakthroughs stall before they reach patients, and what will it take to get them through?

The timing is right. AI can now design molecules, not just screen them. Regulators, from the US FDA to India's drug authorities, have opened the door to human-cell testing. And the WHO has set targets for vaccine patches that survive at least three days at 40°C.

We put the question to three IAN portfolio founders, each building from India at a different stage. Two things stood out before we even reached their solutions:

● The science is rarely the bottleneck anymore; translation is. Across all three fields, the core science works. The hard part is making it reproducible, scalable, affordable and acceptable to regulators.

● The industry makes its biggest bets on its thinnest evidence. Drug developers commit billions based on data that, in the words of Biodimension's Ranjith, "does not predict human outcomes." Peptris's Venkat calls the available experimental data "a single drop in an ocean of possibilities."

Here they are, in their own words.

Padmaja Ruparel, Co-Founder, IAN Group

Founder's Lens

Every medicine begins with a search through a space almost impossible to picture. Venkat explains why that search is so hard, and why the answer is smarter AI, not bigger AI.

The gap

"Traditionally, developing a new drug requires over 12 years and $2.6 billion, with the preclinical phase alone consuming 4–5 years and up to $600 million. Because experimental interaction data is like a single drop in an ocean of possibilities, attempting to solve this gap through brute-force R&D or off-the-shelf large AI models creates severe bottlenecks."

Why it matters

"For patients suffering from rare diseases, oncology, and severe inflammatory conditions, this inefficiency translates into decades of unaddressed unmet medical needs."

What we're building

"At Peptris, we address this data asymmetry using a proprietary, automated AI discovery engine (pepAI). Operating on a virtual, 'fabless' model, we computationally design diverse, synthesizable molecules and leverage a global ecosystem of Contract Research Organisations (CROs) for physical validation. This approach enables us to discover validated Preclinical Candidates in ~18 months at less than 2% of traditional pharma costs. By advancing a balanced pipeline of Novel Chemical Entities (NCEs), drug repurposing (such as our DMD [Duchenne muscular dystrophy] asset, PEPR124, which received USFDA Orphan Drug Designation), and rescue molecules across Oncology, Inflammation, and Rare Diseases, Peptris proves that smart algorithmic generalization can transform global healthcare."

Stitching it Together

Though they work at three different stages, all three founders answer the opening question the same way: what's missing isn't the science but the evidence, infrastructure and scale to carry it forward. Peptris is closing a data gap at discovery, Biodimension an evidence gap at testing, and Innovodigm an access gap at delivery.

2 more takeaways:

● Affordability is designed in from the start. Peptris's fabless model runs at under 2% of traditional pharma costs. Biodimension makes human tissue models in India rather than importing them with only days of usable life. Innovodigm's patches aim to loosen the cold chain's grip. That's no coincidence: building from India, where cost and reach come first, makes affordability part of the architecture, not a later discount.

● These are platforms, not single products. pepAI spans new, repurposed and rescued molecules. Biodimension's tissue know-how is moving from testing towards repair. VaxEasy™ starts with Hepatitis B but is built to extend to measles-rubella, HPV and rabies.

Most striking is how candid all three are about what remains unproven: patches need long-term stability data, regulators don't yet consistently accept human tissue models, and AI must generalise rather than memorise. Those are the milestones to watch.

That translation, not science, is now the bottleneck, and it also shapes how IAN invests. Backing good science isn't enough. Founders need capital patient enough to wait for data that can't be rushed, and investors who can read the science, regulatory path and commercial case together. India has too few: only 10–15% of its VC firms have deep pharma and biotech expertise, versus around 60% in the US.

That gap is why IAN built BioAngels with BIRAC. India's first sector-focused angel group for biotech, medtech and healthtech, it is a public-private partnership by design: angels and domain experts bring capital and commercial judgement, while BIRAC brings technical expertise and research infrastructure. The aim is money, mentoring and market access for science-led founders in one place, plus readiness for larger follow-on rounds. It's also why IAN led or co-led rounds in all three companies, from Innovodigm's seed to Peptris's Series A.

90% of targets with no drug. Nine in ten candidates failing in humans. 14.3 million children unreached. Increasingly, the science of better health is the science of closing those gaps: finding the right molecule sooner, knowing earlier whether it will work, and getting it to everyone who needs it.

If you're building anywhere along this journey, IAN would love to hear from you.

You can reach out to us at media@iangroup.vc