232 Episoden
- In this episode of AI For Pharma Growth, Dr Andree Bates speaks with Nijat Ahmadov, CEO of Nucs AI, about molecular imaging as one of pharma’s most underused data assets.
Nijat explains why PET, CT and other molecular imaging data remain largely “untouched”: clinically valuable and created at scale, but still too often trapped in qualitative reads rather than structured, standardised data that can support decision making. As radioligand therapies expand in oncology, that gap becomes harder to ignore.
The conversation explores how AI can help turn molecular imaging into computable, decision-grade data for patient selection, response monitoring and companion diagnostic strategy. Nijat argues that AI is no longer a nice-to-have in this space. Without it, pharma risks losing confidence in the outcomes that affect adoption, reimbursement and commercial success.
They also discuss what it will take for AI-derived imaging biomarkers to become regulatory grade: analytical validation, reproducibility, diverse data sets, clinical validation and evidence that endpoints are meaningful, not just technically impressive.
The key message is that imaging is not only diagnostic. Once structured properly, it can reveal predictive signals about disease behaviour and treatment response, making it a powerful asset for pharma teams building the next generation of oncology trials.
Topics Covered
Why molecular imaging is still underused
Turning PET and CT scans into structured data
Radioligand therapy and patient selection
Moving beyond eligible vs not eligible
AI-derived imaging biomarkers
Clinical validation and regulatory trust
Imaging data as a competitive moat
Why prediction matters more than diagnosis
Eularis helps pharma and biotech leaders turn AI activity into board-defensible governed strategy and measurable commercial outcomes.
If your CFO asked tomorrow for the projected return of each major AI initiative - by year, across three years, with explicit adoption, operating cost and redeployment assumptions - could you produce an answer that survives scrutiny?
And if you could: would you know which of those initiatives most moves the company toward the outcomes it's exposed on over the next three years? Those are two different questions, and most organisations can't answer either. A strong initiative-level ROI tells you a project is defensible. It doesn't tell you it belongs among your top five. Capital spent on a second-order opportunity is capital no longer available for a first-order one — and no amount of downstream rigour recovers value that was never strategically prioritised.
The Eularis AI Strategic Blueprint models both levels: a financial case for every prioritised initiative, and a rigorously modelled ranking of which ones create the most material value against your commercial objectives — then sequences them by dependency rather than enthusiasm, with governance designed for pharma's regulatory reality. See what a board-defensible AI strategy contains → eularis.com/ai-strategic-blueprint-for-pharma
About the Podcast
AI For Pharma Growth is the podcast from Dr Andree Bates, helping pharma, biotech and healthcare organisations understand how AI-based technologies can save time, grow brands and improve company results. The show demystifies AI for biopharma leaders, from start-up biotech through to Big Pharma.
Dr. Andree Bates LinkedIn | Facebook | X E229: From Reactive to Proactive: What a QP's Job Should Actually Look Like in 2026
04.08.2026 | 33 Min.In this episode of AI For Pharma Growth, Dr Andree Bates speaks with Jitesh Halai, founder and CEO of OneSC, about what the Qualified Person role should look like in a more proactive, digitally connected pharmaceutical supply chain.
Jitesh explains how many QPs are still forced into reactive work: chasing documents, checking versions, searching inboxes, reconciling batch data across disconnected systems and trying to work out what is holding up release. In virtual pharma environments, where much of the supply chain is outsourced, that burden becomes even heavier.
The conversation explores how platforms like OneSC can create a single source of truth across supply chain partners, giving QPs live visibility of batch status, documentation, review progress and quality signals. Instead of waiting weeks for all documents to arrive before spotting a packaging, leaflet or batch data issue, automated checks can flag risks much earlier.
Jitesh also discusses how AI, OCR and automation can reduce repetitive administrative work, without replacing human judgement. The aim is not to remove the QP from the process, but to give them more time for the work they were trained to do: critical review, risk assessment and patient safety decisions.
The key message is clear: the future QP should not be fighting their mailbox. They should have consolidated batch information, automated signals and the confidence to move from reactive release management to proactive quality oversight.
Topics Covered
Why QPs are stuck in reactive work
Batch review, release and document chasing
The burden of disconnected systems
Creating a single source of truth
Automated checks for earlier risk detection
AI, OCR and automation in quality workflows
Reducing cognitive burden for QPs
Why human judgement still matters
How real-time auditing may evolve
Eularis helps pharma and biotech leaders turn AI activity into board-defensible governed strategy and measurable commercial outcomes.
If your CFO asked tomorrow for the projected return of each major AI initiative - by year, across three years, with explicit adoption, operating cost and redeployment assumptions - could you produce an answer that survives scrutiny?
And if you could: would you know which of those initiatives most moves the company toward the outcomes it's exposed on over the next three years? Those are two different questions, and most organisations can't answer either. A strong initiative-level ROI tells you a project is defensible. It doesn't tell you it belongs among your top five. Capital spent on a second-order opportunity is capital no longer available for a first-order one — and no amount of downstream rigour recovers value that was never strategically prioritised.
The Eularis AI Strategic Blueprint models both levels: a financial case for every prioritised initiative, and a rigorously modelled ranking of which ones create the most material value against your commercial objectives — then sequences them by dependency rather than enthusiasm, with governance designed for pharma's regulatory reality. See what a board-defensible AI strategy contains → eularis.com/ai-strategic-blueprint-for-pharma
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.
Dr. Andree Bates LinkedIn | Facebook | X- In this solo episode of AI For Pharma Growth, Dr Andree Bates explains why “we’re doing AI” is not a credible board answer, and why activity, pilots and steering committees are not the same as strategy.
Dr Andree breaks down two common answers leadership teams give when asked about AI strategy.
The episode explores why crowdsourced use cases often become “use case copying” rather than genuine internal innovation. A pain point may be real, and a pilot may work, but that does not mean it is one of the highest-value AI opportunities for the organisation. Without financial modelling, business-unit submissions are only inputs, not prioritisation.
Dr Andree also outlines four structural conditions that explain why AI investment often fails to realise value: the value prioritisation gap, the decision rights gap, the data ownership conflict, and incentive misalignment. These issues are connected, and if they are diagnosed in the wrong order, the strategy usually fails at the next layer.
The core message is clear: boards do not need a list of AI activity. They need a strategy they can govern, with clear priorities, financial assumptions, sequencing, ownership and metrics that can be tested over time.
Topics Covered
Why “we’re doing AI” is not a board answer
Activity, demand and value: the difference that matters
Why business-unit use cases are not strategy
Use case copying and internal innovation theatre
The value prioritisation gap
Decision rights between pilot and production
Data ownership and access conflicts
Incentives, adoption and rational resistance
What finance needs to see before funding AI
What a real board-level AI answer sounds like
Eularis helps pharma and biotech leaders turn AI activity into board-defensible governed strategy and measurable commercial outcomes.
If your CFO asked tomorrow for the projected return of each major AI initiative - by year, across three years, with explicit adoption, operating cost and redeployment assumptions - could you produce an answer that survives scrutiny?
And if you could: would you know which of those initiatives most moves the company toward the outcomes it's exposed on over the next three years? Those are two different questions, and most organisations can't answer either. A strong initiative-level ROI tells you a project is defensible. It doesn't tell you it belongs among your top five. Capital spent on a second-order opportunity is capital no longer available for a first-order one — and no amount of downstream rigour recovers value that was never strategically prioritised.
The Eularis AI Strategic Blueprint models both levels: a financial case for every prioritised initiative, and a rigorously modelled ranking of which ones create the most material value against your commercial objectives — then sequences them by dependency rather than enthusiasm, with governance designed for pharma's regulatory reality. See what a board-defensible AI strategy contains → eularis.com/ai-strategic-blueprint-for-pharma
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 E227: From Bench to Boardroom: How One Geneticist is Quietly Reshaping the Future of Healthcare
21.07.2026 | 33 Min.In this episode of AI For Pharma Growth, Dr Andree Bates speaks with Bret Bostwick from Breyer Capital about the rare path from genetics, clinical medicine and drug development into venture capital, and what that perspective reveals about the future of healthcare innovation.
Bret shares how the release of the Human Genome Project first pulled him into genetics, and how clinical work with patients made the science deeply practical. As a medical geneticist, he saw families finally receive a diagnosis, but often without a treatment option. That experience led him towards programmable therapeutics, RNA-based medicines and the translational work required to move from biological insight into human trials.
The conversation explores what makes a therapeutic company investable beyond the science alone. Bret explains why breakthroughs often fail not just because of technical risk, but because the right people, culture, operating experience and business model are not around the table. For him, one of the first questions is not simply “does the science work?” but “what problem is this company really solving, and is this the most elegant solution?”
They also discuss where AI is overhyped and underestimated in medicine. Bret is sceptical of claims that AI can compress a 12-year clinical development journey into two years, because biology still requires time to evaluate safety and efficacy. But he sees enormous potential in agentic AI across the full healthcare and pharma stack, from discovery and preclinical design to manufacturing, commercialisation and patient finding.
The key message is that the future of healthcare will belong to people and companies that can bridge disciplines: genetics, computation, medicine, product development and investment. The biggest opportunities may sit at the intersections, where scientific insight, platform thinking and practical translation come together.
Topics Covered
Moving from genetics and clinical medicine into venture capital
Lessons from RNA therapeutics and translational medicine
Why target genetics matters in drug development
What investors look for beyond the science
Why the right team and culture are critical
Platform companies vs single-asset thinking
Where AI can and cannot compress drug development
Agentic AI across pharma and healthcare workflows
Founder mistakes when pitching healthcare investors
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.
AI platforms and tools solve specific problems. Strategy makes sure you’re solving the right ones, in the right order. If you want help mapping priorities as you evaluate what to roll out next, send me a LinkedIn DM starting with ‘PRIORITIES’ and two lines: what’s already in flight, and the decision you’re trying to make next.
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 | XE226: The AI Deal Scout: How Machine Intelligence Is Reshaping Biopharma Business Development
14.07.2026 | 28 Min.In this episode of AI For Pharma Growth, Dr Andree Bates speaks with Smbat Rafayelyan, founder and CEO of Bioneex, about how AI is reshaping biopharma business development, deal scouting and asset evaluation.
Business development has traditionally relied heavily on relationships, conferences, databases, analyst reports and manual search. But as therapeutic pipelines, publications, patent filings and global biotech activity expand, that old model is becoming harder to sustain. Smbat explains why teams that only rely on their network risk missing valuable assets before they even know they were available.
The conversation explores how AI can act as a deal scout, helping biopharma and VC teams identify, structure and evaluate opportunities faster. Smbat explains how Bioneex allows biotech companies to submit non-confidential asset information, while AI extracts, validates and compares that data against external sources, curated databases and market intelligence.
They also discuss where AI is most useful in the BD process. The aim is not to replace human judgement, but to reduce the overwhelming search space. If AI can narrow thousands of potential assets down to a small, relevant shortlist, expert teams can spend their time on the work that matters: diligence, strategic fit, deal judgement and human relationships.
Smbat also warns that AI is not magic. General-purpose language models are not enough for serious deal sourcing. Effective AI scouting requires structured data, validation, multiple specialised models, human review and infrastructure built specifically for biopharma business development.
Topics Covered
Why traditional deal scouting is too slow
The limits of relationship-led deal flow
How AI supports asset search and evaluation
Matching biotech assets with pharma and VC priorities
Why structured and validated data matters
AI use cases beyond drug discovery
Narrowing thousands of assets into focused shortlists
Failure modes of general-purpose AI in BD
How BD teams may change over the next few years
Why human judgement still matters in due diligence
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.
AI platforms and tools solve specific problems. Strategy makes sure you’re solving the right ones, in the right order. If you want help mapping priorities as you evaluate what to roll out next, send me a LinkedIn DM starting with ‘PRIORITIES’ and two lines: what’s already in flight, and the decision you’re trying to make next.
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
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Über AI For Pharma Growth
AI For Pharma Growth is the podcast from pioneering Artificial Intelligence entrepreneur Dr. Andree Bates created to help Pharma, Biotech and other Healthcare companies understand how the use of AI-based technologies can easily save them time and grow their brands and company results.
This show blends deep experience in the sector with demystifying AI for biopharma execs from biotech start-ups right through to big pharma. In this podcast, Dr Andree will teach you the tried and true secrets to building results in a pharma company using AI and alert you to some fascinating new tools and applications to benefit you and your company.
As the author of many peer-reviewed journals in pharma AI, and having addressed over 500 industry conferences across the globe, Dr Andree Bates uses her obsession with all things AI, futuretech, healthcare and pharma to help you to navigate through the, sometimes confusing, but magical world of AI powered tools to achieve real-world results.
This podcast features many experts who have developed powerful AI-powered tools that are the secret behind some time-saving and supercharged revenue-generating business results. Those who share their stories and expertise show how AI can be applied to Discovery, R&D, clinical trials, market access, medical affairs, regulatory, market research, business insights, sales, marketing, including digital marketing, and so much more.
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