By Ashu Singhal

Ashu Singhal
Ashu Singhal

President Biden’s executive order to advance our national bioeconomy highlighted the tension between the amazing scientific innovation over the last 10 years and the need for our biotech infrastructure—the underlying scientific systems, manufacturing capacity, and teams—to keep pace. One could see the metaphor to our crumbling infrastructure of highways and bridges, and recognize it is time to modernize our biotech infrastructure.

Today’s reality is that many patients are unable to access everything from basic  treatments for the flu to complex cures for diseases like cancer. As an example, with CAR-T therapy for multiple myeloma, just 25% of patients were reported to receive the life-saving therapy. Only 17 U.S. manufacturing centers produce CAR-T therapies for multiple myeloma, having a total of one to two manufacturing slots each, per month. We haven’t figured out how to scale our biomanufacturing process yet, and drug manufacturers and regulators continue to feel the pain of these challenges, while patients experience the real loss.

We need to build the systems that will serve our bioeconomy now and for the next 30-plus years, and I believe that technology and digitization can and should play a larger role. I come at this from the perspective of founding Benchling, a technology company that serves the biotech industry. I’ve seen firsthand that real collaboration and deep integration between biotech and technology is still nascent.

But now is the time to push that relationship forward. The power of the tech industry is in its ability to make complex systems simple, accessible, and scalable.There is no better challenge for tech to meet than modernizing biotech and biomanufacturing infrastructure. By March 2023, the Department of Health and Human Services has been tasked with coming back with the near-, medium-, and long-term biotech and biomanufacturing priorities for the executive order, and tech must play a role. Looking at the bottlenecks in the bioeconomy, many of the advancements already developed in the tech industry can be put to work today. We don’t need to build from scratch.

Here are three places where I believe technology and biotech can more deeply intersect to modernize our biotech infrastructure.

Digitize biomanufacturing bottlenecks to increase efficiency and speed

Paper and spreadsheets are the enemy of scale, and unfortunately these are status quo in biomanufacturing today. When a recipe for manufacturing a new product is handed over from lab to production, the recipe includes the processes, equipment, materials, and parameters—for large molecules, there are hundreds, if not thousands, of variables in a production recipe. This handover, known as tech transfer, is happening via static spreadsheets, on pen and paper, even over the phone, and can add as much as 18–24 months to time to market.

Now, apply FAIR data principles to this, which create standards for biotech data to be easily found, accessed by those who need it, interoperable between disparate systems, and reusable. While FAIR has focused mostly on R&D to date, these principles can and should also be applied further down the product life cycle with process development and commercial manufacturing, and therefore during tech transfer. Adopting FAIR principles in biomanufacturing would drive consistency in data across teams, make it easier to search, find, and share data throughout the tech transfer, and allow for real-time and well-documented adjustments to recipes that are easily traceable and audited.

To be enacted, FAIR needs modern, cloud-based, data platforms that allow for data organization, collaboration, and easy data sharing. It is impossible to reach FAIR data standards and seamless tech transfers if we continue to rely on disparate, legacy systems which were not designed with these concepts in mind. The tech industry excels in building cloud-based platforms that scale data and data management—this is a challenge that tech can rise to meet today.

Recruit the best in tech to biotech

Fewer and fewer technologists are going to be inspired by optimizing ad clicks. Former Google CEO Eric Schmidt echoed this sentiment: “If I were starting out again today, I wouldn’t focus on bits and bytes alone…the next big thing is the bioeconomy, not the internet.”

There’s an explosion of data in R&D labs, where data now exists in petabytes, making science computational and data-driven, and demanding new skills of workers. Biden is building specialized schools and suggests on-the-job skills training to help scientists learn the ropes of programming. While these initiatives will certainly help, a massively talented pool of highly skilled data scientists, engineers, and programmers already exists in tech. They are competitively sought-after (demand is four times higher than supply for certain roles), but biotech can win this talent.

Why? Talented engineers are attracted to those big, audacious challenges with potential for real-world impact, and biology has arguably the most interesting data and software challenges of this century. Biotech is an industry that’s working to cure disease, combat climate change, and eliminate hunger. It’s also an industry where technologists have recently made massive contributions, whether it’s getting COVID vaccines and treatments to market faster or making unprecedented advancements in predictive AI, like AlphaFold. This is where biotech shines and must stand out with recruiting.

Science is undoubtedly the next frontier opportunity—the tech bio revolution is coming. Now is the time for tech workers to bring their skills to bear to help accelerate biotech.

Tackle biotech cybersecurity & the cloud at the onset

The executive order earmarks $200M to enhance biosecurity and cybersecurity of biotech and biomanufacturing and makes a strong link to our national security. Focusing on cybersecurity in particular, biopharma companies are routinely targeted and attacked by advanced threat actors. In 2021, 98% of pharmaceutical companies experienced at least one intrusion (i.e. security incident). This doesn’t mean that all of those companies had their IP stolen, but it does mean a threat actor was active inside their systems.

While biopharma has some of the highest consumer safety ratings, it does not stack up as well from a cybersecurity perspective, due to lagging investment in security and legacy technologies. A lot of biotechs are still adhering to a security strategy from the late 1990s, using on-premises technology and essentially using firewalls as the first and only line of defense.

Managing cybersecurity risks appropriately today requires engineering, automation, real-time analytics, threat intelligence, significant tooling, and more. Modernizing a company’s cybersecurity architecture takes a tremendous investment and requires changes in team and culture that are often out of reach.

The advice I give biotech institutions is to look at how many other industries have taken advantage of the economies of scale that mature cloud computing providers can offer on cybersecurity, resiliency, and disaster response. Tech cloud providers have a duty and incentive to be secure—they invest far more in security than most biotechs can afford to do on their own, and also have an abundance of expertise. At Benchling as an example, we update the security of our code and infrastructure daily.

More times than not, maintaining an on-prem strategy exposes you to more risk because 100% of the security responsibility and resourcing is on you. The biotech industry can get a more secure outcome by taking advantage of the economies of scale with cloud platforms.

Fostering a deeper intersection between technology and science

The biggest call-to-action in the executive order: Technology needs to play a bigger part in the biotech revolution:

For biotechnology and biomanufacturing to help us achieve our societal goals, the United States needs to invest in foundational scientific capabilities. We need to develop genetic engineering technologies and techniques to be able to write circuitry for cells and predictably program biology in the same way in which we write software and program computers; unlock the power of biological data, including through computing tools and artificial intelligence; and advance the science of scale-up production while reducing the obstacles for commercialization so that innovative technologies and products can reach markets faster.

The intersection of technology and biotech is going to be the next big thing. This is how we achieve real scalability and efficiency with science, when the two industries work together to build the necessary, modern infrastructure for modern science. Ultimately, we will get the science of today—and tomorrow—into the hands of those who need it, faster.

 

Ashu Singhal is co-founder and president of Benchling.