There are a few key milestones in the life cycle of a biopharma: raising your series A, starting your first clinical trial, going public and, for an increasing percent of companies, launching your first drug on your own. But developing a drug and successfully launching it requires different expertise and exposes the company to different risks. This week we look at the results of drug launches by small companies during the pandemic. We also highlight new drugs to treat obesity, the future of the biopharma office, using artificial intelligence to diagnose rare diseases and gaps in the evidence needed for evidence-based medicine.
Each week, we highlight five things you need to know in the life sciences industry. Here’s the latest.
Over the past decade, more and more companies have decided to commercialize their first drugs themselves instead of being acquired or licensing them to established players. This brings greater rewards if they are successful, but also exposes them to the challenges of launch. Evaluate Vantage looks at recent launches and compares them to both stock performance and sales forecasts. The results have been decidedly mixed, with a few successful launches, however many have experienced headwinds because of the pandemic.
For millions of Americans who suffer from obesity, there are often accompanying social and health repercussions. Sadly, these individuals are often blamed for their conditions due to behavior rather than biological factors, despite decades of studies disproving behavioral causes. Now a new round of highly effective drugs that treat the biological causes of obesity are offering patients new tools to help manage this condition.
Following in the footsteps of their tech peers, some biopharma companies have announced they do not plan to return full-time to offices anytime soon. Instead, they expect to see hybrid models that allow employees the flexibility to work from home or an office depending on the need. This reflects the benefits many employees have seen working from home during the pandemic and will give companies more options when recruiting in-demand talent.
With more than 6,000 rare diseases having been identified, it can be difficult for doctors to correctly identify the cause of a patient’s symptoms. Although the chance of having a specific rare disease is small, in total over 3.5% of the population is thought to be affected by one of them. This presents diagnosing challenges for doctors and can lead to delayed or ineffective treatments for patients. Now, researchers are looking at tools using AI that can better identify the subtle clues to rare diseases.
As doctors globally were faced with the need to treat patients with COVID-19, they initially lacked evidence of what would work and what wouldn’t. As a result, many patients received treatment that seemed to help, but turned out not to be effective. In the wake of this, doctors who focus on basing treatment on hard data have looked at the more than 2,900 trials related to COVID-19 and found that many were too small, duplicative or poorly designed. This reveals significant gaps in trial design and, perhaps, ways to improve.