Company News - April 2026 pt2

STORM Therapeutics Limited raises $56M Series C & moves into Phase 2. (16/04/2026)

A meaningful signal for the RNA-modifying enzyme space.

◼️ Key highlights: • $56M Series C led by existing investors incl. Pfizer Ventures, M Ventures & Taiho • Lead asset STC-15 (METTL3 inhibitor) enters Phase 2 in sarcoma • First patient already dosed • Study designed with potential accelerated approval pathway in mind

◼️ Why it matters: Storm is targeting mRNA methylation - a relatively underexploited mechanism in oncology. METTL3 plays a central role in cancer stem cell biology. In sarcoma, it effectively helps drive tumour growth & survival. If validated clinically, this opens up an entirely new therapeutic angle: → Not just killing cancer cells → But reprogramming malignant progenitor cells

◼️ Pipeline momentum: • Phase 1 showed early tumour regression signals across sarcoma subtypes • Phase 2 now focused on monotherapy positioning • Expansion into other tumour types is clearly on the roadmap

◼️ Bottom line: Storm is one of the few companies pushing RNA epigenetics into later-stage development. If STC-15 delivers in Phase 2 this could become: → A first-in-class approach in sarcoma → And a broader platform play across oncology

Novo Nordisk partners with OpenAI to strengthen its position in obesity (14/04/2026)

Novo Nordisk has announced a partnership with OpenAI to deploy artificial intelligence across its business, spanning drug discovery, manufacturing, and commercial operations.

At first glance, this may read like another incremental step in the growing use of AI across pharma.

However, the timing and intent behind this move are important.

◼️ The broader context

Novo Nordisk is operating in an increasingly competitive environment. Eli Lilly has built strong momentum in the obesity market, with continued innovation across both injectable and oral therapies, alongside recent regulatory progress.

At the same time, expectations for the category continue to expand, with analysts projecting the global weight-loss drug market could exceed $100 billion annually over the next decade.

This is now one of the most commercially significant areas in the industry.

◼️ What this partnership is focused on

Novo Nordisk has been clear that this is not a single use-case initiative. The ambition is to apply AI across multiple parts of the organisation: • Analysing complex datasets to support earlier-stage research decisions • Identifying and prioritising potential drug candidates • Improving efficiency across manufacturing and supply chains • Supporting distribution and broader commercial operations

In practical terms, this is about improving how decisions are made across the business not just within R&D.

◼️ A realistic view on AI in pharma

There is already meaningful adoption of AI across the industry, particularly in areas such as: • Clinical trial site selection and patient recruitment • Data processing and regulatory documentation • Operational and workflow optimisation

◼️ Why this matters

This announcement reflects a broader shift taking place across pharma. Companies are moving away from isolated AI pilots and towards more integrated, enterprise-wide deployment.

The differentiator is unlikely to be access to AI itself but rather how effectively it is embedded into day-to-day operations.

◼️ Final thought

For Novo Nordisk, this partnership is less about an immediate competitive response and more about strengthening execution over time.

In a market of this scale, small improvements in speed, efficiency & decision-making can compound meaningfully.

AI may not determine the outcome on its own, but it is becoming an increasingly important part of how leading organisations operate and compete.

Contract Research Organisation (CRO)

There’s a lot of discussion right now about a “move from full-service outsourcing to FSP.”(05/04/2026)

But in practice most Sponsors aren’t making a dramatic shift in one direction.

They’re adjusting the balance.

For biotech in particular outsourcing is less about model preference & more about operational reality because with limited internal infrastructure, lean teams & constant pressure to hit clinical milestones, the priority is often reliable, high-quality delivery rather than building complex delivery models.

That’s why full-service outsourcing continues to play such a central role.

It provides a single accountable partner, faster mobilisation & access to established global capability without needing to build it internally.

At the same time as some biotech companies scale, raise additional funding or move into later phases there is often a gradual shift in how they think about control, visibility & long-term efficiency which is where elements of the FSP model can start to become more relevant.

Not as a replacement.

But as an extension.

For large pharma organisations, the dynamic is slightly different.

With more established infrastructure & broader pipelines there is greater opportunity to selectively embed external talent into internal teams, allowing for increased oversight, consistency across programmes & more flexible resource management over time.

But even here decisions are increasingly made at a study, function or portfolio level rather than applying a single model across the board.

Because FSP while offering control & alignment also requires strong internal governance, steady demand & the ability to effectively manage distributed teams whereas full-service models can offer a more strategic, streamlined approach & speed but with less direct oversight.

Both have clear advantages.

Both come with trade-offs.

Which is why across the industry, hybrid approaches are becoming more common with Sponsors combining full-service delivery for certain studies or phases alongside functional support in areas where internal capability already exists.

Stepping back this isn’t really a debate between two models.

It’s about aligning outsourcing decisions with where an organisation is today, how fast it needs to move & how much complexity it can realistically absorb.

For many biotech companies full-service remains the foundation.

For others it evolves over time.

And for large pharma - it becomes more of a question of optimisation than necessity.

BIOTECHNOLOGY

The Critical Biotech Hiring Transition Between Pre-Clinical & Phase I (08/04/2026)

One of the most important inflection points in biotech hiring comes as companies move from early pre-clinical work into IND-enabling activities & Phase I readiness.

Up to this stage, teams are intentionally lean: • CEO/Founder • Chief Development Officer • Small, experienced board

Supported by CROs, advisors & fractional specialists.

As companies move closer to the clinic, the focus is not on building a large organisation but on introducing targeted capability to support clinical execution & meet increasing regulatory expectations.

The question becomes:

How do we build enough internal expertise to run Phase I effectively while maintaining capital efficiency?

Typical hires include: • Head of Clinical Development or CMO • Clinical Project / Program Lead • Regulatory leadership • Select CMC / manufacturing oversight

Alongside this, many introduce commercialisation advisors to shape early product positioning & long-term value.

Why this matters:

Phase I introduces significant operational & regulatory complexity while also laying the foundation for future clinical & commercial decisions.”

The model typically evolves into: Small internal team Clinical & regulatory leadership CRO execution Targeted external expertise

Where a strong balance is often achieved: • Early regulatory alignment • Hiring for execution, not hierarchy • Introducing commercial thinking at the right stage

Where challenges can arise: • Hiring too quickly • Treating regulatory as secondary • Overbuilding ahead of need

Progressing into Phase I is less about scaling headcount & more about evolving the operating model in a controlled way.

Many companies approach this by treating hiring as a series of timed capability decisions aligned to clinical, regulatory & future commercial milestones.

China Biotech: From Domestic Strength to Global Intent (06/04/2026)

China has long been embedded in global clinical development but it is now operating at an entirely different strategic level.

What’s happening now is not a rebound - it’s a repositioning.

And it’s materially different.

China is no longer competing on volume alone.

It is building towards global relevance.

Over the past decade - China has transformed into the world’s second-largest pharmaceutical market (>$180B) and now contributes ~25–30% of global clinical trials - a significant increase from less than 10% in the early 2010s.

But the real shift isn’t scale.

It’s strategic ambition.

Chinese biotech companies are increasingly: • Advancing first-in-class & differentiated assets particularly in oncology, cell & gene therapy & immunology

• Leveraging accelerated domestic regulatory pathways (NMPA reforms have reduced approval timelines by ~30–50% in many cases)

• Designing development programmes with global regulatory endpoints in mind (FDA, EMA alignment from early phases)

And importantly they are not all taking the same route.

What’s emerging is a clear dual-track development model:

Domestic-first execution Generating early proof-of-concept rapidly within China’s clinical ecosystem often with faster patient recruitment & lower operational costs.

Global expansion strategy Leveraging early data to out-license, co-develop or independently expand into US/EU markets once clinical validation is established.

At the same time:

• Some programmes remain China-only, driven by regulatory, IP or data localisation considerations

• Others are designed as global studies from day one, particularly where asset differentiation supports it

For CROs, biotech partners & investors this creates a fundamentally different operating environment.

You are no longer supporting execution alone.

You are supporting globalisation strategy.

And that brings new layers of complexity: • Multi-region regulatory alignment (NMPA, FDA, EMA) • Data portability & acceptability across jurisdictions • Evolving supply chain models balancing local manufacturing with global distribution requirements

But with that complexity comes significant opportunity.

Because the companies emerging from China today are:

Not just fast.

Not just well-capitalised (China biotech VC investment >$13B annually in recent years).

But increasingly globally competitive both scientifically & strategically.

We are now seeing a steady increase in China-originated assets being licensed or acquired by global pharma with deal value reaching tens of billions annually across oncology & immunology pipelines.

Bottom line:

China biotech is no longer simply participating in global drug development. It is actively influencing how global development strategies are designed, sequenced & executed.

And for those operating in CRO, partnering or talent - understanding this shift is no longer optional.

It’s a strategic requirement!

AI

AI is moving from the edges of drug discovery into its core infrastructure! (17/04/2026)

A pattern is beginning to emerge across OpenAI, Anthropic and Google DeepMind.

It is still evolving & shifting quickly but the direction of travel is clear enough to matter for pharma, biotech and CROs particularly as regulation, compliance and quality remain central to adoption.

➡️ OpenAI is continuing to explore specialised scientific applications within its broader AI platform. The introduction of GPT-Rosalind, a reasoning model designed for biology, drug discovery and translational medicine, reflects growing focus on supporting early-stage research workflows.

The model is optimised for areas such as protein & chemical reasoning, genomics and experimental planning and is currently in research preview with organisations including Amgen, Moderna, the Allen Institute & Thermo Fisher.

The broader signal is the increasing role of AI in shaping how hypotheses are generated and evaluated while still needing to align with the quality standards and validation expectations required in regulated R&D environments.

➡️ Anthropic is expanding its position in healthcare with a strong emphasis on enterprise deployment, safety and regulated settings. It has launched Claude for Life Sciences and Healthcare, spanning use cases from preclinical research through to clinical and regulatory workflows and has brought Novartis CEO Vas Narasimhan onto its board.

There are also reports of a ~$400m stock acquisition of AI biotech company Coefficient Bio, although this has not been formally confirmed. Alongside this, Anthropic has been clear that life sciences is a major strategic focus with efforts centred on integrating models into compliant, auditable systems used across the industry.

➡️ Google DeepMind is operating across both foundational AI and applied science. AlphaFold demonstrated the ability of AI to solve complex biological problems at scale and more recent developments extend into modelling interactions between proteins, molecules and broader biological systems.

Through Isomorphic Labs, these capabilities are being applied within drug discovery, with partnerships including Novartis and Eli Lilly. This reflects a model that connects advanced AI research directly with pharmaceutical R&D, while also facing the same requirements around validation, reproducibility and regulatory acceptance.

Each of these frontier labs is investing heavily, iterating quickly and engaging directly with the life sciences ecosystem.

Their approaches differ but all are moving closer to core scientific and operational workflows.

The opportunity is significant but so is the requirement to ensure that AI systems meet the standards expected in regulated environments, including data integrity, transparency, validation and quality.

The Strategic Shift in Life Sciences AI: From Capability to Control (07/04/2026)

Life sciences is entering a new phase of AI adoption.

Not just tools.

Not just models.

But integrated, agentic platforms that can orchestrate workflows, connect data & support decision-making across the enterprise.

Recent launches including IQVIA.ai show how quickly this category is maturing.

But the bigger point is not any single platform.

It is the shift in what the Industry now requires from AI.

The opportunity is clear: • Reduce manual, repetitive work • Accelerate research & analysis • Coordinate complex workflows across functions • Enable faster more confident decisions

The strategic issue is not whether AI can be used in life sciences.

It can.

The strategic issue is whether it can be deployed at scale within a regulated quality framework.

In our industry - outputs do not stop at dashboards.

They influence decisions that ultimately affect patients.

That means compliance, regulation & quality are not “features.”

They are baseline operating conditions.

No debate. No shortcuts.

This is where competitive advantage will be built: • AI architectures designed for auditability & traceability • Governance models that satisfy regulatory scrutiny • Data foundations with clear provenance & quality controls • Operating models that keep human oversight where it matters

And increasingly data itself becomes the IP.

Not just the volume of data - but the quality, structure, provenance & ability to convert it into trusted, decision-ready intelligence.

In this market, speed still matters.

But trusted execution matters more.

The winners will be the organizations that can do both.

GENERAL ATRICLES

Why inaction costs more than failure (10/04/2026)

Early in my career, I remember sitting on a decision longer than I should have.

Not a bad decision.

Not a risky one.

Just… a move I wasn’t 100% certain about.

So I waited.

Told myself I needed more clarity.

More data.

Better timing.

Weeks passed. Then months.

Eventually, someone else made a similar move.

Not perfectly.

Not with more experience.

Just earlier.

And that was the moment it clicked It wasn’t capability that held me back. It was hesitation.

What I’ve seen since, across pharma & CRO leadership

Failure rarely does long-term damage.

Most people recover quickly.

Adjust.

Move forward.

Inaction is different.

It’s quieter.

It doesn’t show up as a clear mistake.

But it accumulates over time - missed opportunities, slower progression, decisions made too late.

The pattern is consistent

People wait for certainty.

But certainty is usually a byproduct of action not a prerequisite.

They overestimate the downside.

And underestimate how adaptable they actually are.

They aim to get things right first time.

Instead of getting things moving.

The reality

Starting rarely feels comfortable.

But neither does looking back and realising you waited too long.

One is a short-term discomfort.

The other stays with you.

A question worth asking

What are you currently sitting on? A decision. A conversation. A move you know you should probably make.

If you leave it another 3–6 months… does it get easier?

Or just later?

Bottom line Most people don’t fall behind because they fail. They fall behind because they hesitate.

Because over time the biggest risk isn’t making the wrong move. It’s not making one at all.

GLP-1 is no longer a category (10/04/2026)

It’s a strategic platform reshaping the future of pharma.

But what’s becoming clear

This isn’t just a scientific story.

It’s a commercialisation, access & scale story.

The leaders didn’t just build drugs. They built ecosystems.

Novo Nordisk & Eli Lilly created: • Physician education at scale • Patient demand & awareness • Reimbursement pathways • Global supply infrastructure

That’s what turned GLP-1 into one of the most commercially important therapy areas.

Now Lilly has shifted the conversation again

With FDA approval of Foundayo™ (orforglipron) - its oral GLP-1.

And this matters for three reasons: • Small molecule vs peptide → simpler, more scalable manufacturing • No injection barrier → expands into primary care & broader populations • No waiting requirements → can be taken immediately, improving adherence

This isn’t incremental.

It’s a commercial unlock.

Because the next phase is about reach

This market now sits at the intersection of patient need and consumer behaviour: • Patients are more informed, proactive & engaged in treatment decisions • Consumer dynamics (brand, access, convenience) are influencing demand • Digital and direct-to-patient channels are accelerating awareness

At the same time, access is still controlled by: • Medicare / Medicaid dynamics • Private payer coverage decisions • Employer-sponsored healthcare models • Global reimbursement frameworks

Winning here requires understanding both:

Clinical pathways & consumer behaviour.

The next wave understands this • Boehringer Ingelheim & Zealand Pharma → next-gen metabolic combinations • Amgen → differentiated mechanisms • Pfizer → re-entering with renewed focus • Verdiva Bio → emerging metabolic innovation • Structure Therapeutics → oral innovation • Viking & Altimmune → combination strategies

This is no longer just a question of efficacy, safety & tolerability

It’s about positioning, differentiation & scalability.

Manufacturing is becoming a strategic advantage

Peptides: • Complex • Capacity constrained • Expensive to scale

Small molecules (like Foundayo™): • Simpler to manufacture • More scalable globally • Better suited for high-volume demand

This shift has real implications for access, pricing & margin.

And then there’s talent

Because none of this happens without the right people.

Demand is rising for: • Clinical leaders in metabolic disease • Regulatory experts navigating evolving pathways • Manufacturing leaders who can scale globally • Commercial teams who understand both disease and patient/consumer dynamics

And the reality

The best talent is already in seat.

Bottom line

GLP-1 started as a breakthrough.

It is now a platform.

But the companies that win won’t just have better science.

They’ll have: • Stronger commercialisation strategies • Payer access expertise • Deep understanding of patient & consumer behaviour • Scalable manufacturing • And leadership that can execute across all of it