2027 · Hotel Palace Berlin
AIO
Artificial Intelligence Officer Circle
Who governs. Who decides. Who is accountable.
The Thesis
Why This Programme
Who governs. Who decides. Who is accountable.
Every board in life sciences is asked the same question: who is accountable for the AI outcome. The role most boards will appoint does not yet exist at scale.
Technology moves faster than leadership. Boards know they will appoint the role; few yet have the candidate. Models without governance drift. Pilots without accountability stall. The line between AI ambition and AI outcome is the officer who carries both.
The AIO Circle convenes the leaders preparing for that role — across drug discovery, R&D, manufacturing and supply — before the queue forms.
The Through-Line
Closed-door. By invitation. Early. A circle for the leaders preparing for the role before the queue forms.
The models are deployed. The officer is not yet appointed.
The AIO Circle is built for the leaders who close that gap — in drug discovery, R&D, manufacturing and supply.
The Anchor
Who governs. Who decides. Who is accountable.
The officer who carries both.
Conference Chair
Dr Harsukh Parmar
Former SVP, Global Head of Research & Early Development
EMD Serono / Merck KGaA
AIO Feature · Day 2 · 10:30
Potency testing supported by AI. Closed-system automation running faster than manual governance. Chain-of-identity data at every handoff. Release decisions following algorithmic recommendations — and a patient on the other end of every one of them.
The AIO feature asks who governs the intelligence layer when the consequence of failure is not a retracted study but a patient who does not receive their therapy. Day 2 · 10:30–12:00.
Partnership & Sponsorship
The AIO Circle offers a limited number of partnership positions for organisations shaping AI governance, drug discovery, R&D, manufacturing and supply. Featured keynotes, sponsored sessions and curated 1:1 programmes deliver strategic visibility within a room of senior end-user leaders.
Day One
The Manufacturing Decision
Vector, cell, scale and the capacity question
The System That Delivers the Therapy
- Why the approved therapy is not the finish line — it is the start of the manufacturing and supply challenge the room is here to solve
- The vein-to-vein framework: where the chain breaks today and where this programme focuses
- What a decision made in this room changes for a patient at the end of the chain
The AIO Circle exists because approval does not equal access. The leaders who close that gap are in this room. Dr Parmar opens by naming what is at stake.
Viral Vector at Scale: What Actually Breaks When You Move From Clinic to Commercial
- The upstream decisions that determine downstream yield — cell line selection, media development and process parameter control at manufacturing scale
- Potency and purity at scale: where analytical methods that work at Phase I fail under commercial pressure
- CDMO accountability when the sponsor does not own the process — the contract structure that protects patient supply
Viral vector manufacturing is the bottleneck behind every CGT approval. The leaders who solve it first will determine which therapies reach patients and at what speed.
Autologous to Allogeneic: The Economics That Drive the Manufacturing Decision
- The cost-per-patient calculus: where autologous CAR-T becomes economically unsustainable and where allogeneic must prove it has solved the immunogenicity challenge
- Closed-system processing and automated cell culture — what changes in a GMP facility when the operator is removed from the loop
- The manufacturing platform decision that determines your supply architecture for the next decade
The therapy model determines the manufacturing model. The manufacturing model determines patient access. This decision cannot be revisited cheaply once infrastructure is in place.
Coffee & Networking
Autologous vs Allogeneic: The Manufacturing Debate That Cannot Be Deferred
- The clinical evidence, the cost structure and the CDMO capacity that make this choice a strategic commitment, not a scientific preference
- Where the manufacturing platforms diverge — and where shared infrastructure between programmes creates shared risk
- What the room needs to decide before the next programme reaches Phase III
Every CGT programme will face this debate. The organisations that resolve it with discipline — not default — will build supply chains that serve patients at scale. The ones that defer it will face the consequences at approval.
Moderated by Dr Harsukh Parmar, EMD Serono / Merck KGaA
Chain-of-Identity in a Cold Chain World: Where the Vein-to-Vein Journey Actually Breaks
- The logistics handoff points where patient identity data, cell viability and temperature control converge — and where they separate
- What vein-to-vein traceability requires operationally: the data architecture, the logistics contracts and the quality agreements that hold the chain together
- When cold chain failure is not a logistics failure but a manufacturing failure — and how accountability is assigned across CDMOs, couriers and the sponsor
A cold chain failure is not a missed shipment. It is a patient who does not receive their therapy and cannot be re-dosed. The supply architecture that prevents this failure is the one the room needs to build before the next approval lands.
Dual-Modality Supply Governance: Managing Cell and Gene Therapy Programmes Across One Infrastructure
- When CAR-T and gene therapy programmes share CDMO relationships, cold chain infrastructure and quality teams — the governance model that prevents one programme's delay from cascading to another
- Regulatory harmonisation across EMA, FDA and MHRA for CGT supply submissions — where the frameworks align and where they create divergent operational requirements
- The portfolio architecture decision: separate supply systems for each modality or shared infrastructure with modality-specific controls
Most CGT organisations are running multiple modalities on infrastructure designed for one. The governance failures that follow — compliance gaps, batch conflicts, CDMO overcommitment — reach patients before the boardroom sees them.
Lunch & Curated Networking
Outcomes-Based Pricing for One-Time Therapies: The Reimbursement Architecture That Unlocks Access
- The payer's perspective on one-time high-cost therapies: what evidence thresholds, follow-up duration and indication scope determine whether a health system funds the therapy
- Payment-at-outcomes models, annuity structures and instalment agreements — which financial architectures are gaining traction across NHS, European payers and US managed care
- The access gap between approval and reimbursement: what happens to patients in the interim and who bears the commercial and ethical cost
A therapy that cannot be reimbursed is a therapy that cannot reach patients at scale. The pricing architecture the room builds into the next programme will determine its commercial viability before it reaches approval.
What Approval Means to the Patient Waiting
- A single case. A single timeline. The gap between FDA approval and the patient receiving therapy — told from the patient's side of the system.
- A deliberate pause in a programme focused on manufacturing and supply — to hold the human reality of every decision made in this room.
The vein-to-vein journey is an operational framework. Behind it is a person who cannot wait for the system to resolve its manufacturing, logistics and reimbursement challenges. This session holds that reality — before the afternoon's technical sessions.
Health System Readiness: What Casgevy's Launch Taught Every Subsequent Approval
- The NHS specialist centre designation model and the infusion site capacity challenge — what happened in Year 1 of Casgevy's commercial launch that the programme had not anticipated
- Staff training, patient selection, monitoring infrastructure and the health system capabilities that determine whether an approved therapy can actually be administered
- What every CGT programme launching after 2025 must embed into their commercial planning before approval
Casgevy was the first. Its launch created the template — including the failures. Every programme entering the market now has the evidence. The room can choose to use it.
Coffee & Networking
What Gene Therapy Manufacturing Can Take From Biologics Scale-Up — and Where the Analogy Breaks
- The shared challenges: upstream process control, downstream purification, scale-up dynamics and quality release — where decades of biologics manufacturing experience transfers directly to CGT
- Where the analogy breaks: chain-of-identity, patient-specific batch release, cryopreservation and the irreversibility of dosing decisions that have no parallel in conventional biologics
- The knowledge transfer that accelerates CGT manufacturing maturity — and the biologics assumptions that must be abandoned before they cause failures
The biologics manufacturing knowledge base represents decades of hard-won process understanding. CGT can accelerate by drawing on it — if it distinguishes carefully between what transfers and what creates false confidence. This structured collision surfaces both.
From Approval to Patient: The System Failure That No Single Organisation Owns
- Manufacturing, supply, reimbursement and health system readiness — four constraints, four owners, one patient who cannot move until all four align
- Where accountability sits when the chain breaks: the contract structures, governance frameworks and escalation routes that determine response time
- The decisions the room is positioned to make that regulators, payers and health systems cannot make for them
The access failure is not a mystery — its causes are known and the room contains the leaders responsible for every one of them. This panel does not assign blame. It assigns ownership.
Chaired by Dr Harsukh Parmar, EMD Serono / Merck KGaA
Gala Dinner
Day Two
The Quality & Governance Decision
Digital, automation, real-time release and the AIO
From System to Decision
Closed Systems, Open Data: Automation That Runs the Process and Analytics That Govern It
- Closed-system bioprocessing as the standard for CGT manufacture — where human contact points become contamination risks and where automation removes them without removing accountability
- Real-time analytics across the closed system: the sensor-to-signature pathway that enables continuous process verification and reduces the time between deviation and detection
- Digital manufacturing architecture for CGT: the MES, LIMS and ERP integration decisions that determine whether process data is audit-ready or audit-risk
Closed-system automation is not optional for commercial CGT manufacture — it is the regulatory expectation. The digital architecture that connects it determines whether quality data supports the release decision or creates it retrospectively.
Real-Time Release Testing: The Quality Framework That Removes the Waiting
- From final product testing to real-time release: the analytical strategy, the process understanding and the regulatory submission that makes parametric release possible for CGT products
- AI-driven QC: where machine vision, spectroscopic methods and process analytical technology converge to reduce release testing timelines from days to hours
- The regulatory conversations with FDA and EMA around real-time release for CGT — what is accepted, what is still being negotiated and where the framework is heading
For autologous CAR-T, the patient is lymphodepleted and waiting. A release test that takes five days is five days that patient cannot afford. Real-time release is not a regulatory aspiration — it is a patient safety imperative.
Coffee & Networking
AIO Feature · Advanced Intelligence Officers
Who governs the intelligence layer when the patient cannot wait
Every Batch Is One Patient. The AI Cleared It. Who Governs the Intelligence That Makes That Decision?
- Potency testing supported by AI. Sterility assurance monitored algorithmically. Chain-of-identity data at every vein-to-vein handoff — the intelligence layer now touches every critical quality attribute in a CGT release decision. The QP signs the batch. The model built the recommendation. No governance framework formally connects them.
- Where the AIO mandate in CGT differs from every other AI governance role: the consequence of a governance failure is not a product recall or a retracted study — it is a patient in lymphodepletion who does not receive their therapy. The irreversibility of that outcome changes every standard the governance framework must meet.
- The three governance gaps every CGT organisation must close before AI-driven batch release becomes standard of care: chain-of-identity traceability across CDMO handoffs, decision boundary definition between algorithmic recommendation and QP accountability, and validation frameworks that FDA, EMA and MHRA will accept.
Casgevy and Lyfgenia are approved. The supply chain is not yet ready to deliver them at commercial scale without governance failure. The AIO role emerges from the manufacturing and compliance reality — not the technology conversation. Every leader in this room already carries accountability for intelligence they did not design and governance they have not yet written. For the patients. We must do better.
From Vein to Vein, From Sensor to Signature: What Is the Intelligence Architecture the CGT AIO Inherits?
- The closed-system automation and real-time analytics stack mapped from in-line sensors through AI-driven QC to batch release decisions — with every governance checkpoint named and every vein-to-vein handoff where chain-of-identity traceability is tested against current capability.
- Data interoperability in a GxP environment: what MES/LIMS/ERP integration requires technically in a CGT supply chain, where integration creates audit-ready intelligence and where fragmentation creates the documentation gaps that regulators find during inspection.
- Real-time release testing, potency prediction and AI-driven sterility assurance: the intelligence systems operating at clinical-batch speed across a supply chain no single organisation fully controls — and the architecture decisions that determine whether the AIO can govern them at commercial scale.
The keynote named the governance gap. This session maps the technical architecture that created it — and that the AIO must inherit. The CGT supply chain runs across CDMOs, logistics partners and clinical sites that none of the organisations fully govern. The AIO is accountable for the intelligence layer that connects them. Substantive technical content. No product demonstration.
Who Governs. Who Decides. Who Is Accountable.
- The quality leader who signs the batch. The manufacturing leader who owns the closed system. The digital leader who built the analytics layer. The CDMO site director accountable for the process. All four now make decisions shaped by intelligence they did not design — and none of their job descriptions acknowledge it.
- The 90-day mandate: governance charter, decision boundary definition, validation framework and accountability chain — the four moves every CGT organisation must make before the next inspection or the next batch failure
- None of the titles in this room contain "AI." All of them now make decisions shaped by it. The AIO is the mandate that connects them.
The panel does not conclude with a vision statement. It closes with a 90-day mandate framework. The room leaves knowing what to do on Monday — not just what to think about.
Moderated by Dr Harsukh Parmar, EMD Serono / Merck KGaA
Lunch & Curated 1:1 Meetings
Your Batch Failed at Commercial Scale. The Patient Was Waiting. What Changes?
- 4–6 leaders per table. Chatham House rules. Single decision in focus.
- The distinction between a manufacturing failure and a governance failure — and who is accountable when an AI-influenced release decision precedes the batch failure
- The crisis response protocol the room does not yet have — and must build before the failure, not after
The first high-profile CGT batch failure under AI-influenced release will test every assumption about governance, accountability and regulatory trust. The organisations that have rehearsed the response will navigate it. The ones that have not will define the precedent for everyone else.
Coffee & Networking
The System Shift: From Quality by Testing to Quality by Intelligence
- Where the CGT quality system must evolve to accommodate AI-influenced release decisions — regulatory submissions, inspection readiness and the audit trail that satisfies an FDA or EMA inspector
- The change management dimension: how manufacturing, quality and digital leaders align around the intelligence layer without the governance framework that would normally precede deployment
- What must change in the next 24 months across CGT manufacturing, supply and quality — the decisions that cannot be deferred until the next programme
This closing session brings every discipline in the room to a single question: what must change before we return? The answer belongs to the room.