We've all heard the promise: AI will transform biopharma strategy. But when we tested leading LLMs (Claude, Copilot, Gemini) on real in-licensing opportunities, they failed 64-77% of the time.
The problem? Off-the-shelf AI lacks three critical elements:
So we built Scitaris-AI differently.
Here we systematically integrated our proprietary intelligence databases, expert SOPs, and PhD-level analytical protocols. The result: up to 95% accuracy and 94% reproducibility in evaluating strategic dimensions like development status, transactability, and competitive differentiation.
Scitaris-AI works as a configurable companion system, enabling our teams to conduct broader, deeper analyses while maintaining the rigor high-stakes decisions demand.
Key takeaway: Reliable AI for pharma strategy requires more than better prompts. It requires systematic integration of domain expertise, curated data, and structured frameworks that mirror how experts actually think.
The inaugural SciCafé event series —held at NYU Langone Health—brought together the insights and energy of an invitation only gathering of New York’s biotech and investment leaders. Featuring scientific talks from Henry Colecraft (Columbia University), Arvin Dar (Memorial Sloan Kettering), and Muzammal Hussain (NYU), along with a forward looking panel discussion, the event explored the breakthroughs and bottlenecks shaping the next generation of therapeutics.
In our first Whitepaper edition exclusively prepared for this event series, Scitaris maps the evolving landscape of Induced Proximity Therapeutics, with a spotlight on targeted protein degradation (TPD). Senior Consultant Marie Klimontova, PhD, examines the field’s dynamic shift toward molecular glues, the expanding role of antibody based degraders, and emerging modality innovations.
The whitepaper also highlights how TPD applications are rapidly moving beyond oncology—propelling BTK degraders to the forefront, unlocking opportunities in autoimmune and inflammatory diseases, and building confidence in CNS directed strategies. Looking ahead, we explore the next wave of induced proximity platforms—from RIPTACs and DUBTACs to extracellular degraders—and consider how these technologies may define future therapeutic paradigms.
To learn more, check out the official NYU event page here.
The inaugural SciCafé event series —held at NYU Langone Health—brought together the insights and energy of an invitation‑only gathering of New York’s biotech and investment leaders. Featuring scientific talks from Henry Colecraft (Columbia University), Arvin Dar (Memorial Sloan Kettering), and Muzammal Hussain (NYU), along with a forward‑looking panel discussion, the event explored the breakthroughs and bottlenecks shaping the next generation of therapeutics.
In this first Whitepaper edition exclusively prepared for this event series, Scitaris maps the evolving landscape of Induced Proximity Therapeutics, with a spotlight on targeted protein degradation (TPD). Senior Consultant Marie Klimontova, PhD, examines the field’s dynamic shift toward molecular glues, the expanding role of antibody‑based degraders, and emerging modality innovations.
The whitepaper also highlights how TPD applications are rapidly moving beyond oncology—propelling BTK degraders to the forefront, unlocking opportunities in autoimmune and inflammatory diseases, and building confidence in CNS‑directed strategies. Looking ahead, we explore the next wave of induced proximity platforms—from RIPTACs and DUBTACs to extracellular degraders—and consider how these technologies may define future therapeutic paradigms.
Biopharma leaders are exploring LLM foundation models to support in-licensing and portfolio decisions, yet the true performance of these tools in high-stakes settings remains unclear.
In this original research article, Scitaris benchmarks Copilot, Claude, and Gemini against 40 expert in-licensing assessments and quantifies how often model recommendations diverge from ground truth.
Senior consultant Wignand Mühlhäuser, PhD, and Scitaris co-founder Jonathan Vonnemann, PhD, show where current LLMs misjudge opportunities even after prompt engineering. They also explain how Scitaris combines curated knowledge and vetted LLM workflows to keep decision quality under tight control while still unlocking value from AI.