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Down on the Pharm

At GeneCentrix, we are a big believer in intelligence. Specifically, with respect to drug

discovery, we believe that important data is not being used to guide and rationalize drug

discovery efforts, and that the key failure is in productive integration of heterogeneous data to generate insights. Our specific focus, as readers have probably already appreciated from perusing our newsletter and our website, is on the integration of pharmacologic/ chemistry data on drug targets with genomic/biology data on tissues and cells to provide an in vivo (“body map”) context to drug action.

We had an opportunity to step back and see how our view sits in the bigger picture through the recent roundtable put together by That’s Nice. Biotech and pharma leaders were asked what the biggest challenge facing the industry was.

Out of 51 responses, nearly half (23, 45%) focused on logistics as the key challenge. This

included manufacturing and supply chain challenges, as well as sustainability and process improvement through digital/AI/automation technologies. The impression was left that there was a fear that productive technologies were not be used to their utmost in drug development, as well as the impression that these respondants skewed more towards pharma and existing

medicines rather than biotech and new medicines. The effect of COVID-19 on the supply chain was a frequent citation, suggesting that the pandemic revealed weaknesses in the logistics of pharma. Some respondents explicity framed this challenge as being about the cost of manufacturing medicines, which is probably the bottom line for this view, especially in the face of pharma pricing pressures.

Interestingly, our view was shared by only about 1/3 (15, 30%) of the respondents, almost universally innovative, high tech informatics-centric startups and biotechs . . . like us. The explosive growth of useful data and its underutilization was frequently cited, as expected. In particular, the use of human data was explicitly cited as a key asset. A corollary of this focus, as it is for us, is the benefit of patient stratification and precision medicine. Namely, that matching drug activity to specific patient phenotypes is a huge opportunity. For us, that matching is proposed to operate through the lens of the target tissue or cell: understand that better and how that target tissue or cell is different from the others in the body and, if you take advantage of that information in designing your drug, you will have a better drug that gets approved more easily (and with less cost!).

The third most frequently cited area (9 respondents, 17%) was the clinical area, namely clinical trials, but also patient indications, health inequities and geographic or phenotypic markets. It is a bit surprising that this was not the most common answer, since clinical trials are the most costly and also the most frequent point of failure in drug development, but clearly most of us

feel that the writing is already on the wall by the time a clinical trial is underway and the place to intervene is earlier.

Finally, another surprise, personnel talent (1, 2%), policy/regulation (1, 2%), and competition/funding (2, 4%) were rarely cited as the biggest challenges, but of course these are the most fundamental, general business challenges, not specific to the pharma/

biotech industry.

So, we are not alone, but it looks like we are on the innovation/emerging/high-risk end of the spectrum. Not a bad place to be, since that’s where the breakthroughs tend to happen.


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