Artificial Intelligence and Outsourcing Impact Bioprocessing Operations – Genetic Engineering & Biotechnology News
Artificial Intelligence (AI) is being incorporated into every aspect of 21st century bioprocessing, and much of its impact will depend on how it is managed,” according to Rathin Das, PhD, CEO of Synergys Biotherapeutics. “Because of its power, it is currently having a weighty effect on efficiency and reproducibility, which will profoundly affect the management of personnel,” he said.
Das was chief brand officer for North American operations for Affitech, a company that researches and develops therapeutic vaccines (pharmaccines) for chronic diseases, before striking out on his own with Synergys, which targets tumors with anti-angiogenic proteins. As a CEO, Das is no longer at the lab bench, but he is well aware of the changes that have transformed laboratory procedures. “Today we see vast improvements in sensitivity; a l µL blood sample can be diluted 10 million times to picomolar levels, and with robotic automation guided by AI, one can obtain extremely accurate data,” he explained. “So it is no longer necessary to do many repetitions, averaging them to obtain statistically significant results.”
This means that staff can move faster, can be more productive, and with a nimbler work force, impressive savings can be realized.
The other major transformation driving Bioprocessing 4.0 is the rise of outsourcing to contract manufacturers. “Twenty years ago, there was no way that I could contract out my research,” Das continued. “The expertise was simply not available. But today we have excellent, extremely specialized contract manufacturing organizations (CMOs) with high quality resources, staff and instrumentation. For instance, when I do pharmacokinetic studies, I simply give them the specifications, and they apply their expertise.”
Because there are numerous high quality CMOs out in the bioprocessing landscape, competition is fierce, noted Das, and is of high quality and reliable. “When we do cost benefit analysis we can pick and choose the supplier for the best outcome,” he said.
For Das, AI is an enabler of precise management at all stages of bioprocessing: in the research and development phase, and in the stages of upstream and downstream production on the way to the final product.