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Yearly Archives: 2024

February 16, 2024 no comments

Lessons from Monte Carlo Models: Why Drug Development is Hard

“There is more than one way to skin a cat” is a rather gruesome British idiom, but its sentiment surely applies to running a successful pharmaceutical portfolio.  It is now more than a decade since Francesco De Rubertis, together with Kevin Johnson and Michele Olier, coined the term “asset-centric” investing to describe the approach to portfolio creation that still underpins the strategy at Medicxi.  And today it has earned its place in the lexicon of life science venture capital, playing a key role in generating returns of investment houses across the globe.

But it is not universal.  Indeed, many highly successful investors adopt strategies that are close to the opposite of “asset-centricity”, with large Series A rounds behind pipelines or platforms.  And even the fathers of asset-centricity themselves have said on many occasions that the approach is not suited to all kinds of assets or opportunities.

What then determines the “right” model?

The same Monte Carlo models that a decade ago helped DrugBaron refine the concept of asset-centricty can provide insight into the conditions under which an asset-centric strategy “wins”.  Doing that requires a quick review of the those models (described in much more detail here and here).

The system being modelled is shown in Figure 1.  Synthetic portfolios are created in silico, where each asset has a hidden flag as to whether it “works” or not (because, in the real world, whether an asset can be successful or not is fixed before you invest – we just don’t know which ones work until after we work them up), with X% of the assets marked as working.  A sum is then invested in each asset ($Y) and thereafter a decision is made whether to kill or continue the asset – and crucially this decision has a false positive rate (A%), where it keeps going assets whose hidden flag indicates eventual failure, as well as a false negative rate (B%) where it kills assets marked as “working”.

This cycle is then repeated multiple times, and once a fixed sum has been invested, the remaining live assets are monetised, with those that work delivering $Z and those that do not being worthless.  The total sum realised compared to the total invested estimates the return on that portfolio.  You can run the model with lots of synthetic portfolios with different conditions (X, Y, Z, A and B can be varied), comparing average and range of returns to optimise the strategy.

What this taught us that returns are most sensitive to costs, particularly during the early iterations (such that it rarely makes sense to pay extra for more information, even if it modestly improves the quality of the decision filter).  It also …

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November 22, 2022 no comments

A quite revolution in the world of proteomics

Proteomics – examining the panoply of proteins within …

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July 19, 2022 no comments

How to find a drug: the past, present and future of small molecule drug discovery

Despite the current hype around so called “advanced …

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February 7, 2022 no comments

Re-Imagining Med Chem Strategies: the Tyranny of the n+1 Compound

Finding small molecule drugs is much harder than …

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May 24, 2021 no comments

Why Small Beats Big: the Hidden Cost of Too Many Voices

The coronavirus pandemic has taught us a lot …

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February 16, 2021 no comments

The history – and the future – of antibody discovery technologies

Monoclonal antibodies are now well-established as a mainstay …

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January 8, 2021 no comments

Why Sarepta’s most recent failure in DMD was entirely predictable

Yesterday, Sarpeta (NASDAQ: $SRPT) announced that its gene …

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January 2, 2021 no comments

One dose or two? What the debate about COVID vaccination teaches us about science – and its limitations

Over the past week a furious debate has …

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November 9, 2020 no comments

The Hidden Superpower of Strategic Focus

The first death unequivocally caused by COVID was reported to …

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April 14, 2020 no comments

COVID19: Serology is harder than it looks

More than a month after the World Health …

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