It’s time for more tech and biotech innovation in 2023 –

[ad_1]

The drive to make the UK a science powerhouse was central to the government’s announcement ending 2022, which has appointed five industry experts to lead the sectors most vital to the UK’s future innovation. As Chancellor of the Exchequer Jeremy Hunt said: I want British companies to lead the world in turning fantastic science into new products and services and we need to make sure government is doing all it can to encourage innovation and competition.

For biotechnology to achieve our societal goals, we must build the foundational systems that support modern science. Government investment will be key. Technology resources will also be critical in overcoming current technical skills gaps to modernize how we move new cell and gene therapies out of R&D and introductory manufacturing, to ensure scientists are poised for success with artificial intelligence for drug discovery. I come to this from the perspective of a technologist working in the biotech industry, and the trends I focus on involve applying the technology industry’s prowess for innovation to the biotech industry’s biggest bottlenecks and needs. of the basic systems.

1. AI has unintended consequences for biotech, and that’s a good thing.

The biotech industry is starting to see real progress with AI-focused drug discovery companies hitting significant milestones or clinical trial readouts Relay Therapeutics and Recursion are two examples. These successful reads are catalyzing greater investment in the space. In the last 12 months alone, big pharmaceutical companies have closed $20 billion in AI-powered drug discovery deals, spending hundreds of millions up front. This is also driving more partnerships between pharmaceutical and AI players, with 67 partnerships in 2021, a threefold increase over the past three years (GlobalData, 2022).

For an industry that has historically valued solitary discovery or collaboration around a single molecule, AI is creating a large surface area for collaboration and partnerships in biotech, and also requires labs to collaborate on huge datasets.

AI in biotech will be a driving function for biotech to accelerate the hiring of data scientists and AI and ML roles and to create better data standardization and stronger digital data backbones. These changes will not only benefit the application of AI and ML in biotechnology, but will lead to improvements in scalability and efficiency in research and development in general.

2. Bioproduction, not just biological research, will become the focus of innovation

The reality today is that many patients are unable to access everything from basic treatments for influenza to complex cures for diseases such as cancer due to limitations in bioproduction.

With CAR-T therapy for multiple myeloma as an example, the average wait time for a treatment slot is seven months, during which time the cancer can progress to a point where it will no longer be beneficial. Bioproduction is a major bottleneck here. There aren’t enough CAR-T manufacturing facilities, and the manufacturing process for these bespoke treatments, which are based on patients’ unique cells, is often entirely manual. Manufacturing sites rely on pen and paper to capture all production data – this not only slows things down, but also introduces more error potential than digital systems.

If record keeping can be made entirely electronic and easily shared among all stakeholders in the manufacturing process, such as the hospital, shippers, and drug manufacturers, CAR-T cells could be produced at an estimated 40% rate . Innovative biotechnologies are starting to address this problem.

3. Tech workers leave big tech for biotech and don’t look back.

More than 150,000 workers around the world have recently left technology and are looking for the next opportunity. They’re looking for more meaning, more impact, and a bigger challenge.

Biotechnology is the next big thing. Not crypto, not the metaverse. Technologists are realizing that biotechnology offers the most exciting data and software challenges of this century. They want to work on breakthrough innovations with potential real-world impact, and biotech is an industry that cures disease, fights climate change, and eradicates hunger.

It’s also an area where technologists have made a huge contribution recently, whether it’s getting COVID vaccines to market faster or making unprecedented advances in predictive AI, like Generate Biomedicines’ Chroma. And this is only the beginning. The superpower of technology lies in making complex systems simple, accessible, and scalable. Tech workers have spent decades transforming industries with a cloud-first, digital and data-driven approach. Now they are leaving technology for the love of technology and applying the lessons learned at the R&D lab.

Tech workers have the skills biotech needs today. Biotech will build on this momentum and ramp up the hiring of data scientists, ML experts, and software engineers.

About the author

Ashu Singhal is co-founder of Benchling. Since he co-founded Benchling in 2012, Ashu has overseen the company’s rapid growth. As co-founder, Ashu is responsible for driving product development and strategy, helping scientists increase their productivity, collaborate more effectively, and achieve new data-driven insights. Prior to Benchling, he co-founded a social media analytics company which was acquired by Twitter. He holds degrees in computer science and mathematics from the Massachusetts Institute of Technology.

[ad_2]