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AI Is Moving Biotech’s Bottleneck
Biosimilars get strategic, biotech’s bottleneck shifts downstream, and life sciences faces the AI ROI test.
Gaston Brizuela Bosio
September 23, 2026
Good morning, ! This week we're covering how biosimilars are becoming an active cost-management tool, why AI is shifting biotech’s bottleneck from discovery to development, and the growing pressure on life sciences companies to prove AI’s ROI.
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Join PE150 and Caplink for our AI & Data Insight Breakfast in London. Register here.
DATA DIVE
Biosimilars Are Moving From Adoption to Active Cost Management
Biosimilars are becoming a more deliberate cost-management tool, but payer strategies remain fragmented across pharmacy and medical benefits. 63% of respondents use a lowest-net-cost strategy across the pharmacy benefit or both benefits, while only 6% apply that approach exclusively to the medical benefit.
The bigger shift is toward steering utilization. 63% of respondents mandate biosimilars for new patients through the pharmacy benefit or across both benefits, compared with 52% that require existing patients to convert from reference biologics through those channels.
For investors, the opportunity extends beyond biosimilar manufacturers. As adoption expands, payers will increasingly need infrastructure to manage formulary decisions, benefit coordination, reimbursement and patient transitions. That creates room for specialty pharmacies and other service providers positioned between manufacturers, payers and patients.
The bottom line: Biosimilars are becoming another lever in the specialty-drug cost-control toolkit — and the complexity of implementing those strategies is creating value downstream.
Continue reading HERE
HEALTHTECH CORNER
AI Is Moving Biotech’s Bottleneck
AI is making drug discovery faster. The rest of biotech hasn’t caught up. McKinsey’s Technology Trends Outlook 2026 highlights how AI-enabled biological design is expanding the number of promising candidates researchers can identify. But discovery is only the front end: wet-lab validation, clinical evidence, manufacturing and regulatory approval remain difficult to compress.
That shifts the industry’s constraint from finding candidates to processing them. Life sciences and bioengineering attracted $101B in equity investment in 2025, with investment hovering around $100B for the past three years. As AI increases discovery throughput, value may increasingly migrate downstream—to the platforms and infrastructure that can validate, develop and commercialize those candidates faster.
Why it matters: The next biotech race may be less about who discovers more—and more about who can move promising candidates to market faster.
You’re invited: Where AI Meets Private Equity
Artificial intelligence has moved beyond experimentation. The real question for private equity firms is no longer whether to adopt AI, but how to turn it into measurable value across the investment lifecycle.
On November 18, PE150 and CapLink Group will host the AI / Data & Insight Private Capital Breakfast, an invitation-only gathering at London's May Fair Hotel that will bring together operating partners, deal teams, portfolio executives, and technology leaders to discuss what AI adoption actually looks like inside private equity.
The morning will feature three practitioner-led discussions:
AI Into Value Creation — How leading firms are transforming AI from dashboards into repeatable value creation playbooks across portfolio companies.
AI Across the Investment Lifecycle — Practical applications spanning sourcing, due diligence, investment decisions, and portfolio management.
Building the AI-Enabled Private Equity Firm — The operating models, data strategies, and organizational capabilities required to scale AI successfully.
Interested in attending? Register or request the full agenda here.
Interested in sponsoring? Email [email protected]
COMPETITIVE LANDSCAPE SNAPSHOT
TREND TO WATCH
AI’s Next Test: Proving the ROI
Life sciences companies have spent the last few years figuring out where to deploy AI. Now comes the harder part: proving it actually pays off.
According to Deloitte’s 2026 midyear survey, 71% of life sciences executives said AI deployment had advanced over the prior six months, while 35% reported significant progress deploying agentic AI. Yet the results are considerably less mature: only 45% reported measurable improvements from AI initiatives, and just 13% said those improvements were being achieved at scale.
The gap points to the industry’s next AI bottleneck. As deployment accelerates, companies need to move beyond pilots toward redesigned workflows, clear KPIs and consistent measurement of economic and clinical outcomes. Deloitte also found that 61% of executives view partnerships as particularly important for accessing AI capabilities, suggesting external technology providers will remain central to that transition.
The bottom line: AI adoption is becoming table stakes. For investors, the differentiator may increasingly be which companies can translate deployment into measurable productivity, margin improvement and commercial performance at scale.
