AI For Pharma Growth

On 7 May 2026, the EU reached a provisional agreement to push back the hardest deadlines in the EU AI Act. Many leadership teams heard one message: “we’ve got more time”. In this solo episode, Dr Andree Bates explains why that exhale is dangerous. The timeline moved, but the governance exposure did not.

Dr Andree breaks down what the delay does and does not change. The dates may shift, but the architecture of the AI Act remains intact: risk classification, documentation, oversight, robustness, logging, conformity assessment, and post market monitoring. These are not last minute checklist items. They are operational capabilities you have to build, test, and keep running.

The real risk, she argues, is misreading “more time” as permission to wait. The hardest work is operational: finding every AI system across the enterprise, including vendor embedded AI inside platforms like CRM and workflow tools, distinguishing genuine AI from marketing labels, classifying systems properly, assigning ownership, and building processes that still hold when vendors update models or features under the hood.

She also tackles a costly misconception for US based pharma: the EU AI Act is deliberately extraterritorial. Scope follows where outputs are used, not where the company is headquartered. If AI outputs touch EU employees, regulators, clinicians, or patients, you may be in scope, even if the system is built and operated in the US.

Dr Andree’s bottom line: the companies that treat this runway as time to build will compound governance maturity and deploy faster with less risk. The ones that wait will hit 2027 under compression, with more shadow AI, more remediation, and less credibility when scrutiny arrives.

Topics Covered
What moved in the EU AI Act timeline, and what did not

Why AI governance is an operating model, not a deadline project

The real work: inventory, classification, ownership, documentation

Vendor embedded AI and shadow AI as hidden exposure

High risk obligations and why you can’t assemble them late

Extraterritorial scope and why US pharma is still in scope

What to do with the runway: build maturity, not delay

Eularis helps pharma and biotech leaders turn AI activity into board-defensible strategy and measurable commercial outcomes.If your organisation has plenty of AI in motion but very little that moves the commercial needle in a way the board can see, start with our 10-Day AI Diagnostic Sprint. It’s a focused diagnostic that surfaces what’s actually broken and what’s blocking results, before you invest in a larger strategy effort.

The Sprint diagnoses the problem. The AI Strategic Blueprint that follows is where we build the board-defensible strategy and plan.Details at eularis.com.

If this episode described your situation, send me a LinkedIn DM starting with ‘SENSECHECK’ and two things: the question you’re trying to answer internally, and what’s currently in flight. I’ll reply with what I’d need to see to turn that activity into a defensible plan, and the next step.

About the Podcast
AI For Pharma Growth is the podcast from pioneering Pharma Artificial Intelligence entrepreneur Dr Andree Bates, created to help pharma, biotech and healthcare organisations understand how AI-based technologies can save time, grow brands, and improve company results.This show blends deep sector experience with practical conversations that demystify AI for biopharma leaders, from start-up biotech right through to Big Pharma. Each episode features experts building AI-powered tools that are driving real-world results across discovery, R&D, clinical trials, medical affairs, market access, regulatory, insights, sales, marketing, and more.

In pharma, the biggest deals are increasingly won or lost before a formal process even begins. In this episode, Dr Andree Bates interviews Andrey Doronichev, co-founder and CEO of Bioptic, about the “intelligence gap” in business development, licensing, and corporate strategy, and why many companies are losing opportunities before they even know they’re competing.

Andrey shares how his background building products at Google, including launching the YouTube mobile app, shaped his obsession with making messy, unstructured information usable at speed. He argues that pharma intelligence suffers from a similar problem: critical signals exist across scientific, regulatory, and business sources globally, but traditional approaches rely on relationships, conferences, spreadsheets, and slow manual synthesis.

A key theme is competitive asymmetry. Deal teams are under pressure to source external innovation while the signal landscape expands rapidly, including an increasing share of patents and assets emerging outside the US. Andrey describes a common pattern: teams work from partial databases and manually maintained lists, then discover a competitor has already secured a preferred position with an asset they never saw coming, often in markets where information is harder to access.

Bioptic’s thesis is cadence. If the same landscape work that takes weeks via consultants or days internally can be done in minutes, the operating model changes. Instead of humans acting as data gatherers, they can spend time on the human work: judgement, relationship building, negotiation, and structuring deals. Andrey describes Bioptic as a “self evolving operating system” that can build new integrations and analyses on demand, closing the gap between questions and actionable intelligence.

Topics Covered
Why pharma’s biggest deals are lost before the process starts

The intelligence gap: relationships vs anticipatory signal capture

Global complexity, China signals, and why databases lag

Cadence as competitive advantage in BD and strategy

From spreadsheets to continuously updated intelligence

“Operating system” thinking and building capabilities on demand

Turning analysts from data gatherers into decision makers

What changes for BD teams over the next five years

Eularis helps pharma and biotech leaders turn AI activity into board-defensible strategy and measurable commercial outcomes.If your organisation has plenty of AI in motion but very little that moves the commercial needle in a way the board can see, start with our 10-Day AI Diagnostic Sprint. It’s a focused diagnostic that surfaces what’s actually broken and what’s blocking results, before you invest in a larger strategy effort.

The Sprint diagnoses the problem. The AI Strategic Blueprint that follows is where we build the board-defensible strategy and plan.Details at eularis.com.

If this episode described your situation, send me a LinkedIn DM starting with ‘SENSECHECK’ and two things: the question you’re trying to answer internally, and what’s currently in flight. I’ll reply with what I’d need to see to turn that activity into a defensible plan, and the next step.
About the Podcast
AI For Pharma Growth is the podcast from pioneering Pharma Artificial Intelligence entrepreneur Dr Andree Bates, created to help pharma, biotech and healthcare organisations understand how AI-based technologies can save time, grow brands, and improve company results.This show blends deep sector experience with practical conversations that demystify AI for biopharma leaders, from start-up biotech right through to Big Pharma. Each episode features experts building AI-powered tools that are driving real-world results across discovery, R&D, clinical trials, medical affairs, market access, regulatory, insights, sales, marketing, and more.

Real world evidence (RWE) could transform drug development and clinical care, but most organisations still struggle to turn messy clinical data into decisions they can trust. In this episode, Dr Andree Bates speaks with Dr Danielle Bower, CEO of QuadraticMed, about bridging the “data use divide” between clinical expertise and data science, so real world data becomes usable evidence rather than noise.
Danielle explains why real world data is both more valuable and more difficult than clinical trial data. It reflects broad, diverse patient populations over longer timelines, with richer signals across labs, medications, imaging, pathology, and increasingly digital sources like wearables. But it’s also incomplete, inconsistent, siloed, and collected through real clinical judgement rather than strict protocols.
A core message is that tools don’t replace domain expertise. Danielle shares how data processing without medical context can silently change the meaning of clinical variables, producing flawed conclusions even when the analytics look “correct”. Trustworthy outcomes require the right clinical question, appropriate comparisons, careful handling of missingness, and validation against biological reality.
They also unpack what’s real versus hype in healthcare AI. GenAI is already helping with documentation and summarisation, but the bigger value is using RWE at scale to personalise treatment, detect risk earlier, and improve care efficiency. The main constraint is rarely the model. It’s data quality, governance, and cross functional communication.

Topics Covered
RWE vs clinical trial data
Why real world data is messy but essential
Domain expertise and clinical validation
Data quality, missingness, and contradictions
The real bottleneck: workflow + communication
What GenAI can and can’t do today
Regulation, privacy, and trust
Measuring success in pharma and healthcare systems
Eularis helps pharma and biotech leaders turn AI activity into board-defensible strategy and measurable commercial outcomes.
If your organisation has plenty of AI in motion but very little that moves the commercial needle in a way the board can see, start with our 10-Day AI Diagnostic Sprint. It’s a focused diagnostic that surfaces what’s actually broken and what’s blocking results, before you invest in a larger strategy effort.
The Sprint diagnoses the problem. The AI Strategic Blueprint that follows is where we build the board-defensible strategy and plan.
Details at eularis.com.
If this episode described your situation, send me a LinkedIn DM starting with ‘SENSECHECK’ and two things: the question you’re trying to answer internally, and what’s currently in flight. I’ll reply with what I’d need to see to turn that activity into a defensible plan, and the next step.
About the Podcast
AI For Pharma Growth is the podcast from pioneering Pharma Artificial Intelligence entrepreneur Dr Andree Bates, created to help pharma, biotech and healthcare organisations understand how AI-based technologies can save time, grow brands, and improve company results.
This show blends deep sector experience with practical conversations that demystify AI for biopharma leaders, from start-up biotech right through to Big Pharma. Each episode features experts building AI-powered tools that are driving real-world results across discovery, R&D, clinical trials, medical affairs, market access, regulatory, insights, sales, marketing, and more.
Dr. Andree Bates LinkedIn | Facebook | X

Some of the most powerful breakthroughs happen when methods built for one discipline get turned on another. In this episode, Dr Andree Bates interviews Dr Irina Babina, CEO of Concr, on how computational techniques originally developed in astrophysics are being applied to oncology, helping predict how individual cancer patients will respond to treatment.
Irina shares her journey from genetics and targeted cancer therapy into building applied solutions, driven by a frustration many scientists recognise: good science doesn’t always reach patients fast enough. A pivotal patient experience reinforced her focus on personalised biology, because behind every dataset is a person, and oncology cannot be solved purely through averages.
Concr’s approach is built around Bayesian computation and uncertainty-aware modelling. Instead of assuming clean, complete datasets, the system is designed to work with missingness and fragmentation, updating predictions as new evidence comes in. Irina explains how Concr connects mechanistic biological modelling and preclinical drug perturbation data to patient multi-omics, imaging, treatment response, and outcomes data from both clinical trials and real-world settings.
A key application is Concr’s patient-level digital twin (“Farsight Twin”), which simulates an individual’s probability of response across therapies, estimates likely benefit, and helps stratify patients earlier in development. Irina shares a use case where Concr supported indication ranking from cell line data, then helped interpret phase 1 signal by estimating which patients benefited from the novel drug versus standard of care, enabling sharper inclusion and expansion planning.
Looking ahead, Irina argues we’re moving toward personalised oncology where population-level protocols fade, and decision-making becomes confidence-based, adaptive, and informed by longitudinal monitoring as tumours evolve over time.
Topics Covered
Applying astrophysics-inspired methods to cancer biology

Bayesian computation and modelling uncertainty

Integrating multi-omics, imaging, trials, and real-world evidence

Translational modelling from preclinical to clinical outcomes

Patient-level digital twins and therapy response simulation

Stratification, enrichment, and reducing early-stage uncertainty

Pan-cancer modelling to improve rare cancer prediction

The future of personalised oncology and dynamic monitoring

Eularis helps pharma and biotech leaders turn AI activity into board-defensible strategy and measurable commercial outcomes.
If your organisation has plenty of AI in motion but very little that moves the commercial needle in a way the board can see, start with our 10-Day AI Diagnostic Sprint. It’s a focused diagnostic that surfaces what’s actually broken and what’s blocking results, before you invest in a larger strategy effort.
The Sprint diagnoses the problem. The AI Strategic Blueprint that follows is where we build the board-defensible strategy and plan. Details at eularis.com.
If this episode described your situation, send me a LinkedIn DM starting with ‘SENSECHECK’ and two things: the question you’re trying to answer internally, and what’s currently in flight. I’ll reply with what I’d need to see to turn that activity into a defensible plan, and the next step.
About the Podcast
AI For Pharma Growth is the podcast from pioneering Pharma Artificial Intelligence entrepreneur Dr Andree Bates, created to help pharma, biotech and healthcare organisations understand how AI-based technologies can save time, grow brands, and improve company results.This show blends deep sector experience with practical conversations that demystify AI for biopharma leaders, from start-up biotech right through to Big Pharma. Each episode features experts building AI-powered tools that are driving real-world results across discovery, R&D, clinical trials, medical affairs, market access, regulatory, insights, sales, marketing, and more.

Dr. Andree Bates LinkedIn | Facebook | X

Pharma doesn’t have an AI experimentation problem. It has an AI execution, scaling, and ROI justification problem. In this solo episode, Dr Andree Bates names one of the most expensive failure patterns in the industry: pilot purgatory.
A key theme is misdiagnosis. When AI stalls, organisations often blame platforms, data science capability, training, vendor selection, or “resistance to change”. Dr Andree argues these explanations are usually incomplete because they ignore the structural constraints that determine whether AI gets trusted, governed, adopted, and tied to real decisions at scale.
She outlines the core blockers she sees repeatedly: governance ambiguity, unresolved decision rights between global and local teams, data ownership disputes, incentive misalignment across functions, and adoption friction caused by tools that were never designed around real workflows. Treating adoption as a comms issue or solving with yet another pilot simply keeps the constraint untouched.
Finally, Dr Andree explains what breaking out of pilot purgatory actually takes: clear executive ownership of business outcomes (not just technical delivery), defined decision points where AI changes action, governance that accelerates scale rather than blocking it, cross functional stewardship models, and defensible value logic that survives board scrutiny. The organisations pulling ahead aren’t running the most pilots. They’re confronting what’s structurally broken early, then building a strategy and sequencing plan that makes scale inevitable.
Topics Covered
What “pilot purgatory” is and why it’s so costly

The tell tale signs: pilots, duplication, uneven adoption, decorative AI

Why more pilots can make the stall worse

Common misdiagnoses: tools, training, vendors, “resistance”

The real blockers: governance, decision rights, data ownership, incentives

Why adoption is a downstream symptom, not the core problem

Rebuilding defensible ROI logic and board ready financial models

What “good” looks like when organisations break out of purgatory

Why delay compounds scepticism and weakens transformation capacity

Eularis helps pharma and biotech leaders turn AI activity into board-defensible strategy and measurable commercial outcomes.
If your organisation has plenty of AI in motion but very little that moves the commercial needle in a way the board can see, start with our 10-Day AI Diagnostic Sprint. It’s a focused diagnostic that surfaces what’s actually broken and what’s blocking results, before you invest in a larger strategy effort.
The Sprint diagnoses the problem. The AI Strategic Blueprint that follows is where we build the board-defensible strategy and plan.Details at eularis.com.
If this episode described your situation, send me a LinkedIn DM starting with ‘SENSECHECK’ and two things: the question you’re trying to answer internally, and what’s currently in flight. I’ll reply with what I’d need to see to turn that activity into a defensible plan, and the next step. 
About the Podcast
AI For Pharma Growth is the podcast from pioneering Pharma Artificial Intelligence entrepreneur Dr Andree Bates, created to help pharma, biotech and healthcare organisations understand how the use of AI-based technologies can save them time and grow their brands and improve company results.This show blends deep sector experience with practical conversations that demystify AI for biopharma leaders, from start-up biotech right through to Big Pharma. Each episode features experts building AI-powered tools that are driving real-world results across discovery, R&D, clinical trials, medical affairs, market access, regulatory, insights, sales, marketing, and more.
If you want, I can also pull 3 “quote graphic” alternates that are shorter and sharper from this solo transcript (there are loads of killer lines in here).

Dr. Andree Bates LinkedIn | Facebook | X