Modern Biotechs Deserve Better Than the Legacy IT Partner Model
By: Alexander Scheer, Co-Founder and Head of Cyber Security
Most biotechs under 150 people run their technology the same way:
A generalist MSP for enterprise IT, cyber security tools (not strategy), projects, networking and tickets,
Perhaps a separate partner for cloud
A vCIO who is usually incentivized to repeat the vendor-driven playbooks that gets companies stuck in the first place
A GxP IT consultant for clinical stage compliance
A “vCISO” who’s one-step removed from a systems administrator or sales person
Rarely does a small biotech have industry-experienced operators steering technology, security, and compliance as a unified program tied to the company's portfolio objectives.
Most companies discover this gap the hard way, typically before an inflection point when the stakes are high, or just after one, when tech-debt induced damage is already accumulating.
This is a broken and legacy model, and it fails almost every time. It does not support the hyper-competitive, lean operating models expected of biotechs today. It won't support what's coming next.
The argument I'm making is straightforward. Many modern biotechs approach R&D by owning critical capabilities like molecular design, assay design and interpretation, and go/no-go decisions, outsourcing commodity execution, and retaining the strategic knowledge and decision-making context that drives iteration inside the company.
That same logic should apply to technology infrastructure.
We spend most of our working hours inside biotech companies. Not as scientists, but as the people shaping and executing their IT and cyber capabilities in support of portfolio objectives. And we've watched, repeatedly, as companies that are rigorous about their portfolio strategies, inadvertently or by design, treat their technology programs as an afterthought.
Why now
The biotech “recession” that began in 2022 forced a significant shift: massive layoffs, a drop in IPO entrants, depressed funding activity. The ZIRP era is long behind us, and the capital markets continue to show clear reluctance toward companies without clinical-stage assets or meaningful proof-of-concept data. What's unfolding is more structural than a typical business cycle.
Biotech venture funding dropped from $7 billion in Q1 2025 to $4.8 billion in Q2 — tied for the worst quarterly total in three years.¹ First financings collapsed from $2.6 billion to just $900 million over the same period, a five-quarter low.² Seed and Series A deals fell to 191 in 2025, down 36% from 298 in 2020, capturing roughly 35% of biopharma VC dollars versus over 40% during 2020–2022.³ Capital is concentrating into fewer, larger rounds.
Meanwhile, the competitive landscape has shifted beneath everyone's feet.
Chinese companies accounted for roughly a third of global biotech outlicensing deal value in Q1 2025, up from 8% in 2021.⁴ The aggregate value of deals involving Chinese biotechs nearly tripled from $32 billion in 2022 to over $92 billion by late 2025.⁵ These aren't late-stage cherry picks — 71% of 2024 East-to-West transactions were at the preclinical or Phase I stage⁶, representing a clear pattern in which companies are sourcing innovation earlier in the discovery process from an ecosystem that barely registered in global licensing markets a decade ago.
The U.S. retains clear advantages in late-stage clinical execution, commercial infrastructure, and regulatory credibility. However, the competitive pressure accelerates a conversation that was already overdue…how ruthlessly disciplined can biotechs be in their capital deployment, and is their underlying technology foundation built for how lean and fast they need to move?
The era of building “empires” is over.
A biotech flywheel
Two pieces published earlier this year frame the distinction well.
Abbas Kazimi at Nimbus Therapeutics argues⁷ that the winners in modern drug discovery won't be whoever has the biggest wet lab. They'll be whoever owns the design-make-test-analyze (DMTA) cycle. Nimbus uses CROs and CDMOs for physical execution but retains control of hypotheses, molecular designs, prioritization logic, and every go/no-go decision. The institutional knowledge stays inside the company.
John Cassidy approaches the same problem from the geopolitical angle, arguing that when Western biotechs outsource enough upstream work in the name of efficiency, instead of solely saving money, they’re exporting competitive capabilities. Therefore, what started as cost optimization becomes a transfer of competitive advantage to the very ecosystems now competing with them.⁸
Kazimi's point isn't solely about who does the work. It's about where the learning accumulates. Each DMTA cycle at Nimbus feeds the next one — the institutional knowledge compounds. Fragment that flywheel across disconnected partners and the compounded learning stops, with nobody accumulating the understanding that makes the next decision better than the last.
Cassidy describes the other side of the same problem. When you outsource enough of the work, the capability migrates to the vendor, creating an inherent dependency.
Interestingly, this is often the default state of IT environments inside most biotechs. Disparate, ineffective vendors and no shared context. Each request or issue treated in isolation…each business need handled from a reactive state versus proactively. Standardization versus right-sized and tailored to an organization’s unique preferences, norms, and workflows. The institutional knowledge that should be compounding across the IT portfolio and value streams for a business doesn't exist.
I believe modern biotech operating models require a partner that keeps this flywheel intact, similar to the R&D context as described in the above opinion pieces.
It is a partner that functions as an extension of the leadership and operations team. It is a group that can shift between roles as the business demands, owning the strategic thinking alongside the company, orchestrating execution across whatever combination of vendors, tools, and internal resources makes sense, and taking over the execution directly when speed or quality requires it. A composable team built on secure baselines and proven foundations that operates across the full remit, strategy through execution, and optimizes relentlessly at every level.
The opposite of the templatized, fully outsourced model where nobody builds institutional knowledge and nobody is accountable for what the technology environment actually produces.
The gap between what exists and what's needed
Consider what technology services can generally encompass inside a biotech:
Strategy, business partnership, and technology roadmapping tied to portfolio milestones
Information architecture and data governance (ownership, lineage, quality, classification)
Identity and access management spanning lab and corporate environments
Cybersecurity strategy, detection and response aligned to biotech threat profiles
Lab systems, instrument integration, and electronic lab notebooks
Informatics pipelines
Cloud, HPC, and machine learning environments supporting in silico discovery
GxP-compliant systems and regulatory compliance (data privacy, financial, clinical)
Cost governance and application rationalization
Vendor coordination across the full stack
Technology in a modern biotech touches every function, every data source, and every decision the company makes. In the age of AI, this dependency only deepens.
What the alternative looks like to the legacy model is not particularly exotic.
Bespoke partners that own the relationship end-to-end across the IT remit, experienced in biotech, comfortable presenting strategy to executive management, capable of standing up a compliant cloud environment or embedding AI into business workflows, and just as willing to roll-up their sleeves to solve issues.
In the end, the difference here isn't the list of capabilities.
It's whether someone is responsible for how they fit together, and whether that someone understands the business well enough to build capabilities that work in lockstep with the strategy.
The partner test
A few diagnostic questions for leaders at biotechs navigating this environment — whether you sit in operations, finance, or a G&A role overseeing technology spend:
If you decided to leave your MSP tomorrow, could you? Do you own your tenant, your data, your credentials — or would you discover at the 11th hour that offboarding costs extra and won't be finished before a deadline that matters?
Do you have a resource you can rely on from your current IT partner that goes beyond the gearhead speak?
Can your provider hold a conversation with an auditor, a potential partner's security team, or your board, translating technology to business terms succinctly?
Is the person managing your technology relationship someone who was actually hired to do it, or did the responsibility land on someone in HR, operations, or finance because nobody else was available?
When you last evaluated IT providers, did the options look meaningfully different from each other — or was it the same service in different packaging, competing on price instead of capability?
Are you paying for proactive support, or are you paying for a monthly invoice and an escalation queue?
Can your IT partner envision, clearly create, and present a technology strategy to your management — or do they only surface when something breaks?
Has your MSP ever proactively decommissioned a tool you were paying for but no longer using — or does your spend only go in one direction?
Is anyone aligning your technology roadmap to your business milestones — your IND timeline, your clinical readouts, your partnership strategy — or does IT operate in a parallel universe?
If you can answer these confidently, you're ahead of most. If you can't, the issue probably isn't that you chose the wrong vendor. It's that the model itself was never built for what you're trying to do.
What comes next
The biotechs that rethink their operating model now, not just in R&D but across every function that supports it, won't just survive, I believe they will thrive in a highly efficient manner.
What matters is who keeps the flywheel turning: the institutional knowledge, the design logic, the ability to make decisions from a position of understanding rather than dependence. That principle doesn't stop at the lab bench. It applies to every system that sits between an experiment and a decision, and the technology infrastructure is where most of those systems and data live.
This is the problem we set out to solve at Mantle.
Not by adding another vendor to the patchwork, but by pioneering this flywheel mindset, offering a highly composable model, and being accountable for how it all fits together.
Notes
¹ HSBC Innovation Banking, 2025 Mid-Year Venture Healthcare Report, as reported by BioPharma Dive, "Biotech startup funding dried up in second quarter, HSBC finds," July 17, 2025. biopharmadive.com
² Ibid.
³ J.P. Morgan, Q4 2025 Biopharma Licensing & Venture Report (DealForma data through December 15, 2025). jpmorgan.com
⁴ Jefferies equity research, as reported in Fierce Biotech, "China biotechs 'reshaping' US biopharma as outlicensing deals rise 11%," July 2025. fiercebiotech.com
⁵ Evaluate data, as reported in Fierce Biotech, "Geopolitical pressures didn't dent China biotech deals in 2025," December 2025. fiercebiotech.com
⁶ Nature Reviews Drug Discovery, as reported in GaBI Online, "China-to-West pharma licensing deals surge in 2024," 2025. gabionline.net
⁷ Abbas Kazimi, "Why Owning the Learning Loop Matters More Than Owning the Lab," LifeSciVC, January 27, 2026. lifescivc.com
⁸ John Cassidy, "Sovereign Risk: The Geopolitical Price of Outsourcing the Biotech Engine," jwcass.substack.com, January 2026.
