This week, we spotlight the use of an oral pill for postpartum depression, a change in Meta’s approach to artificial intelligence, and an expedited regulatory review process for medical devices. We also delve into major increases in research and development spending among large pharmaceutical companies. Lastly, we examine the impact of AI on drug development.
Each week we highlight five things affecting the life sciences industry. Here’s the latest.
The U.S. Food and Drug Administration has approved zuranolone, the first oral pill for the treatment of postpartum depression, to be sold under the brand name Zurzuvae. This once-daily pill, taken over 14 days, marks a significant advancement in treating a condition that affects about one in seven new mothers. The approval of zuranolone is seen as a major step forward in maternal mental health, but experts also stress the importance of psychotherapy and addressing social determinants of health in treating postpartum depression.
Meta has disbanded the AI team responsible for creating the ESMFold protein-folding model, a database of over 600 million protein structures, signaling a shift in focus towards commercializing AI products. ESMFold was built to accurately predict full atomic protein structures from a single sequence of a protein. Though the product was not accurate as a competing product, ESMFold was 60 times faster. The move is part of Meta’s broader strategy to align its research with business needs rather than “curiosity projects.”
The Biden administration is contemplating a faster process to review new medical devices for Medicare coverage. The Centers for Medicare & Medicaid Services has outlined its vision for a new voluntary pathway for device review, expected to be released in a proposal in the coming months. The pathway will build on prior initiatives, including “coverage with evidence development,” allowing Medicare to cover technologies if used in approved clinical studies. If the manufacturer agrees, CMS could initiate a coverage review process even before the FDA clears the product, with appropriate safeguards for Medicare beneficiaries. The new principles aim to balance quicker coverage decisions with rigorous evidence standards.
A recent study indicated that R&D expenditures required to get a drug from discovery to approval have increased exponentially over the last 10 years. In 2013, the average drug required spending of $2.8 billion. In 2023, that amount has increased to an average of $6.2 billion. Further, the study indicated that seven out of 16 large pharmaceutical companies have negative R&D productivity (revenue less R&D spend). Researchers believe this significant increase in spending will lead the industry to aggressively explore technological solutions and AI to defray costs of drug development.
Globally, AI is expected to grow to a $900 billion market by 2030. Drug discovery is expected to be a significant component of that market. Incorporating AI into drug discovery has the capacity to significantly expedite and economize drug development. AI can be used for target identification, drug design and virtual screening, though challenges including data quality, safety assurance and intellectual property rights remain. Biotech companies continue to incorporate AI into their daily operations; however, the majority of drug candidates developed using AI are still in pre-clinical stages. The success of these initiatives remains to be seen.
Get more life sciences insights in our industry outlook.