Life science strategic advisory

An asset doesn't have a value.
It has a distribution.

The science sets the shape of that distribution. The economics reads it. We model both together, because in life sciences one determines the other.

Risk-adjusted NPV — 20,000 simulations
Expected value
$0m
Typical if approved
$0m
Chance of zero
0%
Phase I probability of success60%
Phase II probability of success40%
Phase III probability of success60%
Peak annual sales if approved$800m
Why we're called Ax3

Three axes. Most advisors give you one.

Scientists, physicians, economists and financial engineers in the same room. A biologist and an economist reading the same dataset reach different conclusions — and the useful answer usually sits where they disagree.

Axis 01

Science

Molecular biology, pharmaceutical sciences, epidemiology and genomics. Whether the mechanism holds, and what the data actually supports.

Axis 02

Economics

PhD-level economists and market modellers, including World Bank and ILO consulting experience. What a market will bear, not what a report says it will.

Axis 03

Financial engineering

Valuation and deal-structuring experience from industrial-scale negotiation, applied to probabilistic valuation and real options.

What we do

Three pieces of work, in the order decisions get made.

Each stands alone. Run in sequence, each one narrows the question the next has to answer.

Stage 01  /  Orientation

Landscape assessment

Who else is developing against your target, mechanism or indication — and which of them will still be there when you reach the market.

  • Competitor and pipeline mapping by stage
  • Technology and IP positioning
  • Read-across from adjacent modalities
  • Where the field is likely to consolidate
Stage 02  /  Quantification

Market analysis, scientific and economic

The addressable population is a scientific question before it is a commercial one. Diagnosis rates, genotyping coverage and line of therapy decide how much of an epidemiological number you can reach.

  • Bottom-up addressable population
  • Pricing and access by system
  • Probabilistic valuation and risk profiling
  • Sensitivity on the assumptions that matter
Stage 03  /  Decision

Strategic prioritization

Where analysis becomes decision: which indication runs first, which to hold, which partner is worth giving economics away to. Sequencing is usually worth more than selection.

  • Indication sequencing and ranking
  • Partner fit and deal structure
  • Build, partner or divest frameworks
  • Capital allocation across the pipeline
Who we work with

Two audiences asking the same question from opposite ends.

For companies

You know the science. The question is where to point it.

Founders and executive teams deciding which indication leads, what a partner is worth, and how to frame an asset so diligence moves quickly.

  • Indication selection and sequencing
  • Partnering and licensing narrative
  • Market sizing that survives scrutiny
  • Positioning ahead of a raise
For investors

You know the economics. The question is whether the science holds.

Funds and family offices who need the biology behind a pitch assessed independently, and the numbers rebuilt from the ground up before capital moves.

  • Scientific and technical due diligence
  • Independent rebuild of the model
  • Valuation and risk profiling
  • Portfolio-level exposure
Selected work

Two engagements, start to finish.

Client identities are withheld. The methods, the numbers and the conclusions are exactly as delivered — including the parts that told the client not to proceed.

Landscape assessment & indication prioritization

Finding the whitespace in a crowded oncology field

  • ClientAn oncology developer evaluating oncolytic virus therapy
  • Ask“This space is heating up. Where should we actually plant our flag?”
  • OutputLandscape report with a transparent, scored prioritization matrix
7 of 15 indications on the shortlist were genuine greenfield — high unmet need, almost no competition, and biology suited to the modality.

The situation

Oncolytic viruses have gone from fringe idea to one of immuno-oncology's most active frontiers. That's the problem. When a field gets hot, everyone crowds into the same handful of indications — melanoma, head and neck, colorectal, lung. A team entering now doesn't just need to know the science works. They need to know where the science works and nobody else is looking.

Our client wanted that second answer. Not a literature review. A decision.

What we did

We started with the biology, because a commercial call built on shaky science ages badly. We worked through the major viral platforms — HSV, adenovirus, vaccinia, reovirus and others — and the mechanisms that actually drive anti-tumor response, including how oncolytic viruses turn immunologically “cold” tumors “hot” and set them up for checkpoint inhibitors. That gave us a real basis for judging which tumors are a good biological fit, rather than guessing.

Then we mapped the competition — every asset we could find, sorted by clinical phase and by target disease. The picture that came back was the kind of thing that stays invisible until you plot it: a dense cluster of programs fighting over a few indications, and a set of high-need cancers with almost nobody in them. We pulled in the money too — recent financings, big-pharma acquisitions and licensing deals, and where investor attention was actually flowing.

Finally we scored it. The prioritization matrix weighed three things a developer has to trade off: unmet medical need, how crowded the research space already is, and how well the tumor's biology suits the modality. Every indication got a score and a rank, so the recommendation wasn't a matter of opinion — it was something the client could interrogate, argue with, and defend to a board.

What we found

Seven indications rose out of the top-15 shortlist as genuine greenfield plays, several with orphan-drug potential. Soft-tissue and bone sarcoma and neuroblastoma came out on top: high unmet need, very little competition, and tumor characteristics that lend themselves to the modality. Esophageal, renal, prostate and glioblastoma filled out the ranked list, each with its own risk-reward profile spelled out.

The headline wasn't “oncolytic viruses are promising.” Everyone knows that. The headline was a specific, ordered list of where to go first — and why.

Why it mattered

A first-in-class position in a well-chosen indication is worth far more than a me-too program in a crowded one. By tying scientific fit to the competitive gap, the client got a defensible starting point for R&D focus, orphan-drug strategy and partnering conversations — the difference between “we could do oncolytic viruses” and “here's the case for starting with sarcoma.”

Due diligence & business valuation

Putting a defensible number on an early-stage biotech

  • ClientA clinical-stage immunotherapy company, Phase 1 complete
  • Ask“What is this actually worth — and does the deal structure hold up?”
  • OutputTechnology, market, competition and financial due diligence with a full valuation
$505M / $62M business value fully integrated, versus company value under the actual licensing structure — a gap that told the whole investment story.

The situation

Valuing an early-stage drug company is where a lot of analysis quietly falls apart. The asset had cleared Phase 1 — safety, tolerability, oral bioavailability — with an interesting, first-in-concept mechanism and a licensing-based business model. Promising, but promising is not a number. Investors and partners needed to know what the company was worth today, whether the market was as big as the pitch suggested, and whether the proposed milestone-and-royalty scheme was fair to everyone at the table.

Standard discounted cash flow doesn't handle this well. It ignores the thing that defines biotech: at every clinical phase, the program might simply fail. Any honest valuation has to price that in.

What we did

We valued the risk, not around it. We built a real-options valuation model on the company's actual decision tree — the option to abandon after an efficacy failure, the option to switch to a backup molecule after a safety failure. Each path carries its own probability, so the firm's value comes out as a genuinely risk-adjusted expected NPV rather than a hopeful base case with a discount applied on top.

We built the market from the bottom up. Instead of borrowing a top-line market figure, we constructed a demographic-economic model: population projections and incidence rates by age group, the share of patients failing existing treatment, realistic penetration assumptions, and willingness-to-pay anchored to the price of complementary therapies. For the lead oncology indication that produced a current addressable market near $10.3 billion a year; the secondary vaccine indication added its own smaller stream.

We pressure-tested the story. Pricing was sanity-checked against competitor economics and haircut for a competitor the company's own reports had left out. We mapped the competitive landscape, including a near-identical program that had already failed in the clinic — a detail that matters a great deal when underwriting a first-in-concept bet. Commercial strategy, supply chain and IP position were all modelled, with a SWOT to keep the assumptions honest.

We checked both sides of the deal. We didn't just value the company; we modelled the licensing payment scheme and confirmed it was viable and attractive from the partner's perspective too. A deal only closes when the math works for everyone.

What we found

The model returned a business value of roughly $505M for a fully integrated version of the project, and a company value of about $62M under the actual licensing structure. The gap told a clear story: an early investor stepping in at that point could see invested value multiply substantially as clinical risk was retired. We also showed how value climbs as each milestone clears, so the client could see exactly which de-risking events move the needle.

Just as useful were the negatives. Two of the indications the company was excited about destroyed value in our model — one for a thin, low-margin market, the other because the runway to patent expiry was too short to earn back the R&D. Knowing what not to fund is part of the job.

Why it mattered

The client walked away with a number they could defend, a market estimate built from the ground up rather than borrowed, and a deal structure checked from both sides of the table. That's what turns “this looks interesting” into a decision an investment committee can sign off on.

Weighing a deal, a raise, or where to point your pipeline? Start with a 30-minute call →

Team

Scientists, physicians, economists and financial engineers.

Six people across the three axes — molecular biology, pharmaceutical sciences, economics and finance — supported by advisors from Harvard Medical School, the Joint Genome Institute, Mammoth Biosciences and the BioMed X Institute.

How we work

We show you the unknown unknowns.

Not a deck of industry benchmarks. A model you can interrogate, with every assumption named, sourced and adjustable — so when someone challenges the conclusion, you can show them which input they disagree with.

Engagements are scoped as fixed-fee phases with defined deliverables. You know the cost and the output before work starts.

Method

Probabilistic, not point-estimate

Markov decision trees and real options rather than a single discounted cash flow. Development is a sequence of conditional decisions, and the model should say so.

Method

Bottom-up populations

Built from diagnosis rates, testing coverage and treatment lines — not a headline prevalence figure that assumes every patient is found.

Method

Sensitivity before conclusion

We identify the two or three assumptions that actually move the answer, then concentrate evidence-gathering there.

Method

Multidisciplinary by construction

Scientific, economic and financial training on the same team, by design rather than by hand-off.

Start here

Bring us the decision you're stuck on.

A 30-minute call, no charge and no deck. Tell us the question; we'll tell you honestly whether we can help and roughly what it would take.

Typical first engagement: a scoped landscape or market assessment, 3–6 weeks, fixed fee.