DDIF 2026
Intelligence that compounds.
Drug discovery without data architecture fails.
Clinical development without AI infrastructure stalls.
Models without operational deployment are noise.
Discovery without delivery is just research.
For the patients who cannot wait.
12–13 May 2026 · London
Co-Chaired by Dr Harsukh Parmar and Dr Uwe Gottschalk
Dr Laura Matz Opening Key Note
Featuring
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Dr Uwe Gottschalk
Operating Partner, Keensight Capital
Former CSO, Lonza Group
Architect of global biomanufacturing transformation
He leads because he spent three decades connecting discovery to manufacturing reality. From scaling monoclonal antibodies at Bayer to global bioprocessing strategy at Lonza, he knows that therapies fail not from bad science but from bad infrastructure.
Dr Harsukh Parmar
Former SVP, Global Head of Research & Early Development
Immunology & Neurology, EMD Serono / Merck KGaA
120+ molecules from discovery to development
He leads because he has taken more molecules from target to clinic than most companies attempt in a decade. Co-inventor of marketed therapies in oncology and immunology. 250+ publications. The rare scientist who has built what others benchmark.
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Circle Partners
The gap doesn't close with algorithms.
The gap doesn't close with algorithms. It closes with the people who know how to deploy them.
DDIF brings together up to 200 leaders — those who've built the systems, deployed the platforms, connected the infrastructure. Members and invite only.
Not to just present. To exchange. What worked.
What failed. What's next.
90% of drugs fail in clinical trials.
Discovery and development are converging.
Not in science. In constraint.
AI-native drug discovery and traditional R&D face the same imperative: data without deployment fails. Different modalities. Shared architecture. One operating future.
The gap between computational breakthrough and clinical delivery is where therapies stall, companies falter and patients wait.
Foundation models. Generative chemistry. Self-driving laboratories. Autonomous experimentation. Adaptive trials. Real-world evidence. Clinical data platforms. Scale-ready. Smarter partnerships. New pathways.
Genesis Moment -
Why This Matters?
24 November 2025. The White House launches the Genesis Mission — the largest AI-for-science mobilisation since Apollo.
17 national laboratories.
$70 billion in projected savings.
Discovery compressed from years to days.
The infrastructure is live. The only question is who reaches patients first.
DDIF convenes both the platform providers and the leaders deploying them.
Advisory Circle.
The Few Who Lead | GBX Advisory & Keynote Speakers
DDIF is Curated for
Chief Scientific Officers — R&D strategy, portfolio decisions, platform investments
Heads of Drug Discovery, Medicinal Chemistry and Computational Biology — target validation, molecular design, candidate selection
Leaders in Data, AI and Digital — foundation models, generative AI, predictive ADMET, data infrastructure
Clinical and Regulatory Executives — trial design, real-world evidence, regulatory strategy
Also welcome:
CSO · CTO · CIO · VP Drug Discovery · Head of Biologics R&D · Head of Cheminformatics · Head of Scientific Computing · Head of Laboratory Automation · Director of Translational Medicine · VP Clinical Development · Head of Clinical Operations · Director of Biostatistics · Head of Regulatory Strategy · CMO · Head of CGT Manufacturing · VP Cell Therapy Development · CDMO executives: EVP Operations, Head of Client Programs
DDIF 2026 | The Five Pillars of Discovery Intelligence
1
Foundation
The data layer that decides everything.
Your compound library is static. Your assay data is siloed. Foundation transforms decades of R&D investment into compounding intelligence. This is where ELN meets AI. Where LIMS becomes predictive.
2
Acceleration
Acceleration - From 10 years to 10 months.
AI-native companies are compressing discovery cycles by 70%. Self-driving laboratories do not sleep. Foundation models do not forget. Every month saved is a month gained for patients.
3
Autonomy
The lab that runs itself.
Your best chemists spend 40% of their time on repetitive tasks. Autonomy is the shift from human-limited to machine-augmented.
This is not automation.
This is liberation.
4
Translation
The graveyard of good molecules is full of bad data handoffs.
90% of drugs fail in clinical trials. Most failures trace back to discovery. Translation ensures design for developability. Chemistry for manufacturability.
5
Convergence
Where living therapies meet living data.
Cell and gene therapy does not follow the small molecule playbook. Every patient is a manufacturing run. Discovery intelligence without manufacturing intelligence is a molecule that never reaches a patient.
The few committed to closing the gap.
CSO · CTO · Drug Discovery · Medicinal Chemistry · Computational Biology · Data Science · Laboratory Automation · Clinical Development · CGT Manufacturing · CDMO · CRO
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