Biotech and deep tech fair value that holds up
To auditors, CFOs and boards.
The fair value specialist for innovative Life Sciences — under scrutiny.
Accounting
Legal
Tax
A different playbook, applying deep life sciences context & valuation expertise to accounting, legal and tax purposes — where unfamiliar risk, growth and uncertainty often push frameworks to their limits.
Why we are made for this Our take on Life Sciences
Fair value, made consistent
In innovative Life Sciences, the operating reality is often unfamiliar to accounting, legal and tax frameworks. Risk is intrinsic, assets are incomplete, largely intangible, and value evolves through event-driven transitions. Most fair value work in complex biotech and deep tech capital structures gets built by someone who understands either the model or the standard — rarely both, and almost never the decision and deal-making context too.
Our model reflects actual decision-making logic — governance thresholds, strike rationality, conversion optionality. By design, they hold the answer to the next question — from the auditor, the CFO, the board, or the investor — and support negotiation, decision-making and scenario brainstorming at the same time.
Applying standards and formulas mechanically is rarely sufficient. Fair value in Life Sciences requires contextual correctness: understanding how scientific risk, development pathways, business model, timing, governance and market behaviour interact — and which drivers truly matter for the valuation’s specific purpose.
Long experience and longitudinal exposure across life sciences — stages, investor types, deal structures, governance settings — is what allows us to separate, with precision, what is sector- and context-wide from what is genuinely case-specific. Level 3 judgment is reserved for what truly belongs there, and that is exactly what the company should be prepared to own and defend.
Being a specialist in this field requires,
- mathematical depth,
- operational understanding from science to governance,
- clear reading of market behaviour,
applied together. Not in silos.
We address one core question: Is this value right for its purpose, right for its context, and right under scrutiny?
Three things that make the difference
Context-sharp
We start from operational reality. Science, development pathways, contracts, partners, governance and stage-specific risks are assessed together, not in silos.
Complexity-aware
We strip complexity down to what matters. Assumptions, benchmarks and modelling are limited to what is decision-critical for the specific accounting, tax or legal purpose.
Inconsistencies detected early
We detect misalignments early — between assumptions, incentives, timelines and outcomes — and address them before scrutiny does.
When we are engaged
We are engaged in a broad range of accounting, legal and tax situations where fair value is material and sensitive. This includes third-party fairness opinions, complex fair value matters including under IFRS 2, IFRS 9, IFRS 13, IFRS 15, US GAAP, HGB, Swiss GAAP, OECD Transfer Pricing Guidelines, valuation for IP transactions, as well as situations involving latent taxation of value.
We are frequently asked to model, report, review and sanity-check valuations — particularly when assets, structures or stages fall outside standard practice and require specialist judgment, often across jurisdictions.
We are also engaged when fair value is contested, including litigation and dispute contexts, where our ability to reconstruct context, trace assumptions, and identify inconsistencies is critical.
Four core mandate types
Transfer price
Innovative assets changing ownership or jurisdictionjurisdiction — cross-border IP moves, intercompany licensing, cost-sharing arrangements.
Complex contract
Accounting of structured financing and partnering arrangements (CLA, warrants, structured debt, option deals, contingent payments) including rNPV, Monte Carlo and OPM methodologies
IP valuation
Value of patents across territories, use, license or acquisition, inventor interests and ownership stakes.
Incentives and Earn Outs
Non-standard structures, adapted benchmarks, latent taxation and long-term liability projections, earn-outs, ESOP/VSOP on R&D to commercial stage assets, performance-linked arrangements.
Who comes to us — and why
The situations below are the ones we see most often. Each represents a specific set of pressures, a specific kind of complexity, and a specific reason why a generalist approach — or a life-sciences-operations-naïve one — is no longer sufficient.
1. The innovator operating cross-border
Life sciences / deep tech founders — series A, first cross-border subsidiary, IP structuring
Founders building in Europe, raising in the US or Asia — or the reverse. From the first structuring, IP, territory/comapny rights, transfer pricing, fairness opinions and the valuation of incomplete assets are already on the table. What matters is someone who understands the technology, the non-linear trajectory, and what patient capital and pipeline and platform complexity really mean — not as concepts, but from reviewing 100 R&D projects and USD 3–6bn of value every year. Life sciences and deep tech only.
3. Those entering fair value and reporting early
Scale-ups pre-IPO, institutional fund investors, companies preparing for US listing
For companies financed by family offices with genuine experience in these innovative, high risk assets, by US VCs or by institutional consortia — and particularly for those optionaly preparing for a public markets trajectory — the fair value logic and good governance practice starts well before the auditors, i-banks or stock exchange authorities require it. Entering that logic early, is a material advantage, beyond accounting itself. We are regularly engaged at this stage: before the pressure arrives, by clients who already know that the time to build optionality and defensible positions is now.
4. Funds valuing difficult-to-value assets
Early-stage assets, recovery value, close-ending funds with deep tech or biotech
in portfolio
Some assets resist standard approaches: very early stage, narrow sector context, benchmarks that are sparse or unreliable. Generating alpha and beta in life sciences and deep tech requires holding that complexity without forcing premature resolution. For close-ending funds, the architecture adjusts further: assets are managed differently as the fund approaches its timeline, and recycling of value requires its own modelling logic. Longitudinal exposure on early stage and non-linear value development at scale makes it a recurrent pattern for us.
5. Complex incentive structures and earn-outs
Non-standard ESOP/VSOP, IFRS 2 Share-base payments, BD&L performance arrangements, contingent milestones payment, complex trigger events
Earn-out clauses tied to scientific, regulatory, partnering or commercial milestones; stock options; incentive arrangements calibrated to life sciences and deep tech performance profiles — these combine milestone uncertainty, latent taxation and accounting requirements that generic valuation does not address. Contingent payments here are rarely passive events: understanding what it actually takes for one to materialise — how it is structured, governed, and proven — is part of the modelling, not a footnote to it. We have seen most variations.
2. The cross-border financing
architect
International
consortia — US or Asian investors in European assets, multi-jurisdiction
structures
Life sciences and deep tech are international by nature. The financing structures carry significant complexity — and when a structure spans multiple jurisdictions, the fair value requirements, third-party opinion standards and accounting consistency demands escalate together. We understand what cross-border complexity requires in terms of fair value, reporting, independent opinion and advanced modelling. We are brought in precisely because we operate fluently across those boundaries.
6. Structured financing: CLA, warrants, hybrids, royalties
Complex financing
instruments requiring advanced modelling — IFRS 9, IFRS 13, ASC 820
When financing takes forms that standard models cannot read, when because standard accounting frameworks were not built for them. More than debt, not fully equity — convertible loan agreements with embedded optionality, warrants, royalty-based structures, hybrid instruments — the modelling and audit becomes an issue in itself. Monte Carlo simulation, option models, scenario analysis: the selection of method, its grounding in the measurement objective under IFRS 9 and IFRS 13 or ASC 820, and its audit documentation are as material as the result. We produce this with explicit rationale at every step.
7. IP transactions
Patent portfolio, spin-outs, partial licensing, BD&L transactions, investor vs. owner stake
A patent transaction can involve a piece of a patent, several patents across a portfolio, specific territories or defined uses — rented through a licence or acquired outright, for reasons that are always specific to the situation. Valuing any of this requires understanding the relationship between the parties and especially who animates the IP, the operational and financing reality behind the asset(s). We work at the intersection of IP-to-R&D-to deal making strategy, financing logic and financial modelling.
8. Pre-litigation and litigation support
Expert analysis and independent review — private settlement, dispute
When opinions materially diverge, the analytical work requires entirely senior attention. Solutions arise from what was not looked at closely enough the first time. In innovative life sciences and deep tech, a great deal is missed when data analysis is not done at senior level or methodologies stretched to fit a narrative — what is presented as a benchmark may not function as one; calibration that appears objective is often polarised without realising it; a model built to support a conclusion is not the same as a model built to find one. Two opinions are better than one. A specialist who can go further in scrutiny — by experience, not by effort alone — changes what is visible.
Who calls us
We are most often engaged by CFOs, heads of finance, fund managers and family offices — those who have reached the boundary of what standard approaches can handle, and those who want and know how to stay ahead of it. The distinction matters: the most seasoned executives engage early, not under pressure.
For clients with entities based in the DACH region, complex HGB and IFRS situations often bring us to work alongside Amann Advisory GmbH and Thomas Amann himself — HGB and IFRS specialist, a recognised authority on edge cases and leading trainer on complex IFRS for auditors and corporations notably through the practices Accovalist and Finsus Advisory.
More broadly, the professionals who reach out to us — specialty IFRS experts, accountants, specialty lawyers — do so when a situation requires advanced modelling, depth in life sciences, and context-aware judgment that goes beyond their own mandate.
What this delivers
The clients who engage us most effectively understand that fair value is not only an accounting question. It is strategic optionality, governance discipline, and a way of anticipating complexity from a vantage point that has long-term consequences. Their problem is not always the absence of a valuation team — it is finding one that understands a specific context and can operate at that level.
Engaging with IFRS rigorously brings governance principles into the room, not just accounting. In Europe, fair value tends to be underappreciated — historical accounting is quicker and easier. But there is no productive dynamic between accounting and finance without it, and in high risk innovative life sciences, reducing accounting to box-ticking for too long works against the very optionality and governance that these assets require.
Our model and analyses serve dual purposes: resolving the immediate valuation question while giving the CFO, board or investor a sharper lens on value generation and the tensions within the asset itself. That second purpose is where the lasting impact sits.
The Level 3 distinction
Fair value inputs are classified in three levels. Level 1 is a quoted price in an active market — observable, unambiguous. Level 2 is derived from observable inputs, directly or indirectly. Level 3 is what remains: unobservable inputs, built on assumptions, requiring judgment.
In innovative life sciences and deep tech, especially at early stage, almost everything lives in Level 3. It is the norm. The most technically distinctive aspect of our work in fair value is the discipline around Level 3 inputs.
For CFOs and boards
Within Level 3, there is a further distinction: what is stage-specific, context-specific and what is genuinely case-specific, which is what the company should be prepared to own and defend. We reduce the area of judgment to its true core. That clarity streamlines your focus.
For auditors
Accounting standards were not designed for innovative high risk assets — and we understand the tension that creates. We are genuinely sector-specific, including for the earliest stages and the situations that most stress life sciences and deep tech environment. The result is that audits run more smoothly for everyone.
For investors
We model the long game. Assumptions reflect how value actually accretes and dissolves — the decision logic of the next transaction, the next round, the next value inflection point. Our model and analyses hold the answer to the next question before it is asked.
Volume does not produce insight. The most relevant comparable is not always in the same indication — it may share an asset class, a business model, a capital structure, or an R&D stage. Finding it requires knowing what you are looking for.
Deal comparables belong to a moment that has passed. Retro-engineering one means reading beyond the headline — upfront, milestones, total value — to understand what the buyer believed, what the asset narrative was, what the treatment landscape looked like, and how much of that still holds. A deal tells you how far an acquirer was prepared to go for a specific value narrative at a specific moment. Not that they will go there again.
There is also what public databases do not contain. What gets disclosed is a choice — terms selected, figures framed. Many deals never surface at all; other aborted for reasons as informative as the ones that completed. Knowing how deals get operationalised, what makes them surface publicly and in what form, and why others quietly disappear comes from being a practitioner in the field. It nourishes the analytical work in ways a templated approach structurally cannot.
Market comparables — read properly
Market comparables are the reference point most stakeholders reach for first. They are also where the most analytical value is lost.
What we do
Curate by asset class, business model, capital structure and development logic
Retro-engineer deal structure — upfront, milestones, royalties, optionality
Read against disclosure practice and what that signals beyond what is written
Assess each peer individually — what is expected, what has changed or unfolded since
Distinguish volatility territory by stage, structure and listing status
What most approaches do
Screen by sector and stage
Read headline deal value
Rely on publicly disclosed figures
Apply peer group as given
Treat listed and private deal comps uniformly
We separate what is context-specific, buyer-specific, and asset- or strategy-specific — so that what enters the analysis is genuinely comparable, not merely proximate.
The result of our method is a curated set that reflects the specifics of the asset and where it can realistically head. It also feeds directly into Level 3 calibration — so that rNPV, Monte Carlo and option models are not alternatives to market comps, but built on top of them.