BenevolentAI is using machine learning to gather insights from the body of pharmaceutical literature in order to produce new potential drugs, but can it keep top talent?
Roche, the Swiss pharmaceuticals giant, is caught in a race against time. After making a big bet on breakthrough drugs and personalized medicine, the company has spent much of the last 18 months thinking ahead to the challenges that machine learning and artificial intelligence pose to a traditional, integrated pharmaceutical business model.
The discovery of groundbreaking medical treatments may no longer solely rest in the hands of scientists; grassroots R&D efforts combine scientific expertise with the experiences and creativity and horsepower of the masses.
In rural hospitals, critical drugs are often not in stock. Desperate patients and their families are further pushed into prolonged suffering. Feeling they have nothing to lose, some resort to DIY solutions.
As additive manufacturing is applied to drug production at patients’ closest point of sale, we can imagine a world where rural patients purchase out-of-stock drugs within a few hours of visiting a local hospital. What if the hospital had a 3D printer? What if CAD files from global pharmaceutical companies like AstraZeneca were available?
Today, it costs billions of dollars and many years to commercialize a novel drug. Can Deep Genomics leverage machine learning to reduce these cost and time requirements?
Recursion Pharmaceuticals is deploying machine learning to deeply understand the interactions between genes, proteins, and chemicals to inform not only future drug discovery and drug repurposing, but biological life as we know it.
Faced with increased price and regulatory pressures, the pharma industry is forced to look to other avenues for revenue growth, including digitilization of its historically unwieldy and heavily regulated supply chains. Is industry leader Pfizer doing enough in this pursuit?
Connected drug delivery devices are among the many digital supply chain innovations Teva has acquired to drive sales and control operational costs
With the advent of digitalization, the pharmaceutical industry is using information sharing to improve its manufacturing and supply chain efficiency. Pfizer’s creation of the PCMM plant is one way manufacturing may change in addition to gathering provider-level, and perhaps even patient-level, information. But can providers and patients trust Pfizer and other members of the pharmaceutical industry with their data?
Sourcing comparator drugs for pharma research and development process is expensive and there is high risk of receiving a counterfeited drug from a third-party supplier. To reduce these adverse effects, TransCelerate Biopharma started Comparator Network Initiative to introduce a digital platform where companies can source drugs for each other in a safe a quick way.