Silicon Valley's Primary Role in the booming Life Sciences Industry: Ally, Mentor or Angel

The global biopharmaceutical market has been growing at over 7% year to year for the last decade. Its patient care delivery counterpart - the healthcare industry - has similarly been growing at a robust rate. The digital version of those industries is forecast to explode in 2021 with a growth of over 20%.

These industries have, in the last few years, been encouraged greatly by the innovations and interest of Silicon Valley, the most successful district in the post-internet entrepreneurial world in terms of global impact.

Unlike the clustering and growth of technology companies around the Bay Area south of San Francisco since the 1970s that makes up Silicon Valley, the emergence of an ecosystem of companies, venture capitalists and research institutions to exploit the rapid discoveries of the human genome this millennium (since the reference human genome was sequenced) has been more spread out across the globe.

Thanks to the robustness of Cloud Computing environments and its effective use in largely undisrupted data sharing and remote collaboration, this industrial ecosystem now comprises companies not just in the USA but in Canada, UK, China and a number of other countries.

Entrepreneurs and scientists from anywhere in the world could kick off initiatives that could plug valuable output into the evolution and success of this ecosystem in producing new and radically effective ways of discovering drugs and diagnosing and treating disease.

There may still emerge (like in both the Cambridges, in the USA and UK) more high-density clusters of biotech, med-tech, pure technology, AI and biopharma companies, mainly owing to the availability of specialised skills and talent around academic centres of excellence.

A DEEP INTEREST

Silicon Valley players have themselves eagerly jumped into the space – to apply its culture, technology, investing methods, innovation processes and marketing methods - to play a central role in the evolution of the bio-industrial ecosystem. These efforts mostly ride on the data revolution that has been triggered off by large-scale gene sequencing efforts.

Google’s acquisition of DeepMind is a great example of this. The company has, as a result, produced a much-awaited advancement by solving the protein-folding problem, one of the grand challenges of biology.

With such great strides made in Artificial Intelligence technologies to harness the value of data to make new scientific discoveries and make new products, the question really is therefore not if Silicon Valley will significantly shape global biopharmaceutical and healthcare industry, but how and when.

It may be an exaggerated view to claim that Silicon Valley could subsume the Biopharma industry into itself, but the impact of its entry into the space could certainly have significant consequences for the way the industry evolves. This interest and impact span a number of new and emerging areas, including Synthetic Biology, Systems Biology, Precision Medicine, Digital Health, and others.

For starters, though, there has perhaps already been a triggering-off of a change in one critical area: that of Intellectual Property. The focus on IP in the biopharma industry could have already started to shift from patents on chemical or biological compounds to algorithms and copyrights on code, hitherto largely the domain of Silicon Valley companies.

Companies riding on the opportunity of code-based IP in biopharma and medicine are likely to fundamentally alter the dynamics of the industry, using technologies largely produced in Silicon Valley. In fact, DeepMind is reported to have made at least twenty patent filings that involve solutions to AI and protein folding problems, leading this shift in focus.

The impact of Silicon Valley’s entry may be felt at a much broader and deeper level than just registration of IP, though.

ECONOMICS

Opening the doors for new products and services:

Software environments for programming biology, bio-design automation, DNA storage, blockchain-based intellectual property protection, bio-production security, digital patient models for in silico testing;

Synthetic Biology - designing and manufacturing biological parts and systems, reuse and recycling of biological parts, 3D bio-printing;

Savings for the economy:

Disease prevention saves money for patients, employers and insurers and reduces expense needs on public health. In addition, predictability of disease reduces the need for more hospitals and clinics. Before all of that, the drug development lifecycle costs could be reduced to a fraction of current levels, due to digital models for target and drug screening and trials.

Generation of jobs:

Jobs that require unique combinations of biological knowledge, data and information technology skills will spring up to address needs of those new types of companies, products and services listed above.

INDUSTRIAL ECOSYSTEM

Re-shaping of biopharma and healthcare industries:

New services – advanced disease prediction, personalised gene therapy, consultancies and law firms specialising in management of biological engineering and gene-based therapeutic products

Bridging the chasm between Drug R&D and Care:

Healthcare and biopharma traditionally have not had much of real-time integration mainly because of lack of immediate application of real-time integration – drugs get handed over to the market after getting through long periods of R&D, trialling, and approval processes – and lack of priority for sharing personal feedback data from therapies back to the biopharma industry.

This appears to be in for change, with the optimism around personalised medicine. Agile approaches to therapy at the individual or small targeted group level will mean more needs for knowledge and expertise on both sides.

Clinics and drug companies could in future confer in real-time, enabled by high performance analytics over streaming just-in-time information about patient condition and response to therapies. Silicon Valley could provide the technology for this and accelerate the pace of this integration.

New skills, new training needs:

Specialised skillsets will continue to be in demand, but professionals in traditional lab-research may need to acquire proficiency in digital skills, to make the most of digital atlases and prediction tools.

A new type of research leadership and research leaders that understand AI, and can blend traditional research with AI based methods, may become commonplace.

Supply Chain and Partnerships:

More integration across supply chains will create more data for new research and manufacturing partnerships to emerge, between current players (both drug companies and public/private healthcare organisations), analytics technology companies and bioinformatics-driven research organisations.

These partnerships will likely focus on addressing specific medical conditions and specific modes of treatment, besides paving the way for more targeted treatment pathways for those.

Here, Silicon Valley, in addition to supplying the technologies, will actively invest in problem-solving on a grand scale to accelerate innovation in personalised medicine.

TECHNOLOGIES

Medical devices/Internet of Things/Blockchain: to gather and secure patient/ health information in real-time from individuals and society.

Artificial Intelligence: on individual data – computing disease susceptibility, predicting onset of disease, predicting effect of drug and therapy options; on population data – predicting onset of infectious diseases, targeting right sub-populations with new drugs.

Automation: for integrating the supply chain in biopharma and healthcare, manufacturing of advanced products such as synthetic human cells.

INVESTOR EXPECTATIONS

Focus of investments:

Overall, there has been a multi-fold increase in capital in the life sciences markets, at all stages. Google Ventures for example has made over seventy investments in life sciences companies. While there is no one area that is attracting a disproportionately large chunk of this money, like in other industries, Artificial Intelligence-based ideas seem to have a special appeal.

This is certainly not surprising. Venture firms owned by large pharma will however continue to scout for new acquisitions to grow their innovation pipelines, a trend that has been in place for many years.

In future, as precision medicine slowly starts to become a reality, drugs will need to be produced on-the-fly as more real-world evidence emerges about a patient’s pharmacogenetics and response to treatment. This might trigger off a scramble for investments in just-in-time production and manufacturing using 3D printing and related technologies.

Investor behaviour:

Life Sciences will emerge as a fertile ground for SPACs to both raise funds as well as a means for entrepreneurs to sell-out and exit. This is because of the nature of growth and scale-up in the space – unlike e-commerce, life sciences companies typically have a much longer gestation period before they can acquire their first tranche of customers and look to raise higher orders of magnitude funding in their Series A, B and C rounds than their counterparts from other industries.

Whether Silicon Valley VCs and other investors are looking for greater than the typical 10x RoI or become conservative in their expectations out of the life sciences industry remains to be seen.

If investment in AI brings an extraordinary acceleration to the pace of innovation in biopharma and healthcare, when the time comes for waiting-in-the-wings technologies such as nano- and quantum computing to make their mark, investors everywhere, and not just in the Silicon Valley, will have more choice of emerging areas to spread their bets on.

Conclusion

Analysts may claim that Silicon Valley’s role in Biology is to lead the transformation of Biology into Engineering. Even if this idea may have some truth to it, large-scale engineering of biological systems is both not feasible and may be deemed unethical and hence outlawed as they question the very nature of our existence, threatening the natural evolution of life.

However, in the miniscule timeframe of a hundred years or so of human evolution and endeavour that is the 21st century, this amalgamation of interests could lead to a multi-fold improvement in quality of therapy and health in the world at large, boosting lifespans and multiplying populations.

In this process, we will see much change to the shape of life sciences and healthcare industries, to its economics, technologies, and investment priorities.

With the number of areas of innovation that Silicon Valley investment will introduce into the scheme of those industries’ growth, it is likely to play the role of an inspirational mentor driving pathbreaking advances, more than that of an angel (one of many invested in them) or an ally (provider of technology for evolutionary progress).