Bengaluru-based Peptris Technologies has secured $7.7 million in a Series A funding round, a major boost for its AI-driven platform tackling one of biotech’s toughest challenges: streamlining preclinical drug discovery. Co-led by IAN Alpha Fund and Speciale Invest, with participation from Tenacity Ventures, BYT Capital, and others, this infusion positions the 2019-founded startup to push its programs toward clinical trials while expanding its global footprint.

A New Era for Drug Development

Peptris emerges at a time when traditional drug discovery—plagued by high failure rates, ballooning costs, and timelines stretching over a decade—is ripe for disruption. The global pharmaceutical industry spends upwards of $2.6 billion per approved drug, with over 90% of candidates failing in clinical stages due to unforeseen issues like poor efficacy or toxicity. AI promises to flip this script by predicting these pitfalls early, and Peptris is at the vanguard with its proprietary pepAI platform.

Founded amid India’s burgeoning deep-tech scene, Peptris focuses on the “valley of death” between discovery and development. Its technology doesn’t just generate molecules; it simulates their real-world behavior across absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiles. This holistic approach has already yielded novel chemical entities (NCEs) and revived stalled drug candidates through repurposing, saving partners months and millions in R&D.

The pepAI Platform: Precision at Its Core

At the heart of Peptris lies pepAI, a suite of multimodal AI models trained on vast datasets of chemical structures, biological assays, and clinical outcomes. Unlike generic tools that spit out thousands of hits, pepAI employs generative adversarial networks and reinforcement learning to design molecules optimized for multiple parameters simultaneously. It flags high-risk compounds in silico—before lab synthesis—boosting success rates by up to 5x, according to internal benchmarks.

The platform’s edge comes from its “integrated risk scoring,” which weighs molecular stability, binding affinity, off-target effects, and manufacturability in one go. For undruggable targets in oncology, inflammation, and rare diseases—areas where big pharma has struggled—Peptris narrows chemical libraries from millions to hundreds of viable leads. Early programs target protein-protein interactions notoriously hard to drug, with promising hits advancing to in vitro validation.

Peptris also excels in drug rescue: scanning pharma archives for shelf-dropped candidates, it recontextualizes them with fresh predictive models. This has unlocked repurposing opportunities, extending lifecycles of existing scaffolds while minimizing regulatory hurdles for new indications.

Leadership with Proven Pedigree

The quartet behind Peptris blends Silicon Valley tech savvy with deep pharma domain expertise. CEO Narayanan Venkatasubramanian, an IIT Madras alumnus with stints at Goldman Sachs and McKinsey, spotted AI’s potential during his time scaling data platforms. CSO Shridhar Narayanan brings medicinal chemistry chops from Dr. Reddy’s Laboratories, where he led discovery for CNS disorders. CTO Anand Budni, ex-IBM Watson Health, architects the AI backbone, while Chief Data Scientist Amit Mahajan, from Intel’s AI labs, ensures model robustness.

Their synergy shines in quotes like Venkatasubramanian’s: “Our mission has been to harness AI to address meaningful healthcare challenges that enhance quality of life… translating into hope for patients.” This patient-first ethos, rare in pure tech plays, resonates with investors betting on mission-aligned teams.​

Funding Deployment: From Pipeline to Partnerships

Over the next 24 months, the $7.7 million (₹70 crore) will fuel a multi-pronged expansion. Core priorities include advancing three NCE programs and five repurposing initiatives to IND-enabling studies, bridging the preclinical-clinical gap. Team growth targets 50+ hires across biology, chemistry, data science, and AI, with outposts in the US and Europe to tap biotech clusters in Boston and Cambridge.

Business development ramps up too: forging alliances with mid-tier pharmas and virtual biotechs hungry for de-risked assets. Peptris plans co-development deals, licensing its platform for fee-for-service, and spinning out wholly-owned programs for milestone payments. This hybrid model mirrors successes like Insilico Medicine, balancing revenue with IP retention.

India’s ecosystem amplifies these efforts. Bengaluru’s biotech hubs, tax incentives under Startup India, and proximity to contract research organizations (CROs) like Syngene lower barriers. Prior $1 million pre-seed from Speciale Invest in 2022 validated the tech; now, IAN Alpha’s repeat bet signals scale-up conviction.​

Navigating a Competitive Landscape

Peptris enters a red-hot AI-biotech arena, jostling with players like Exscientia (IPO’d at $2B+ valuation) and Schrödinger, whose physics-based simulations command premium partnerships. Indian peers such as Bugworks and CellProtheranostics focus on antibiotics and cell therapy, leaving Peptris room in computational chemistry. Globally, the $50B+ drug discovery market grows 10% annually, with AI subsets exploding post-AlphaFold.​

Challenges loom: AI models crave proprietary data, raising IP battles, while wet-lab validation remains the gold standard. Regulators like FDA demand explainable AI, a box Peptris ticks via auditable decision trees. Economic headwinds could tighten pharma budgets, but cost savings—slashing discovery timelines from 4-5 years to 1-2—make compelling economics.

Early wins bolster optimism: undisclosed partners report 30-40% efficiency gains, with one NCE hitting lead optimization. As pipelines mature, expect IND filings by 2027, milestone cash, and potential M&A from Pfizer or Novartis scouting AI bolt-ons.​

Broader Impact on Indian Deep Tech

This raise spotlights India’s ascent in AI-for-healthcare, with 2026 funding rebounding 3x from 2024 lows. Firms like Niramai (AI diagnostics) and Qure.ai (radiology) pave the way, but Peptris’ preclinical focus fills a void. It democratizes discovery for orphan diseases, where small markets deter big players, fostering inclusive innovation.​

For patients, faster therapies mean quicker access to treatments for fibrosis, neurodegeneration, and immuno-oncology gaps. Environmentally, fewer failed syntheses cut chemical waste, aligning with green chemistry mandates. As Venkatasubramanian notes, it’s about “relief for caregivers and a more accessible future.”​

Peptris stands poised to compound this momentum, turning algorithms into lifelines. In an industry where one breakthrough recoups decades of toil, its AI edge could redefine success from high-risk gamble to engineered certainty.