AI in Administration and Operations I
Most of the administrative functions in healthcare are done electronically nowadays, making AI the perfect tool to “figure out” what to do and to perform activities like completing forms, sending information and scheduling follow-ups. This would bring three economic improvements to the process: first, it would mean fewer healthcare resources, including the time of doctors […]
What are the consequences of a fragmented healthcare system?
THE US HEALTHCARE ECONOMY is valued at almost $4 trillion. If it was a country, it would have the fifth largest economy in the world, and it equates to nearly half of what the entire world spends on healthcare. We can argue about whether that’s a good thing or not and what percentage of it […]
AI in Pharma Medical Affairs and Commercial
Machine learning can also accelerate the regulatory submission process, as the massive amounts of data generated during clinical trials can be captured and effectively shared to collaborate between investigators, contract research organizations (CROs) and sponsor organizations. In pharmacovigilance, huge amounts of structured and unstructured data need to be reviewed so that we can provide oversight. […]
AI in Clinical Trial Operations
AI can introduce key intelligent automation to different processes in the actual running of trial operations. Some examples of this include using AI in monitoring medication adherence, creating digital twins and synthetic arms that help reduce the number of patients needed, and identifying optimal patients for recruitment by analyzing clinical information. Non-adherence often leads […]
Patient Stratification for Clinical Trials
Here, we’re talking about technologies that help with finding, screening, selecting, recruiting and keeping study patients. A variety of AI technologies can assist in this process. You can use NLP on clinical notes as a first pass to find patients with the right stage of disease once you know their diagnosis from the ICD-10 codes. […]
AI in Clinical Trials III
A technique called adaptive design, which relies on a more flexible approach to clinical trials, has become a key trend for researchers tackling COVID-19. Traditional studies are more rigid about endpoints and dosing regimens, while adaptive designs allow researchers to make modifications as the trial progresses. One of the biggest ongoing challenges is that of […]
AI in Clinical Trials II
A big part of doing clinical trials is to aggregate and mine data from a number of disparate sources to enhance the efficiency, quality and success rate of clinical trials. This is done by extracting structured and unstructured data that’s relevant to the design and conduct of the trial. Natural language processing can help us […]
AI in Clinical Trials I
Once you find a promising drug or device, you need to take it through trials. This is another long and complicated process. We need to make sure that these products are safe and effective before they’re prescribed to large numbers of people. So many things about this process are difficult: deciding which patient population would […]
AI in Drug Discovery V
The companies focused on using AI in drug discovery fall into two categories: Information engines and disease models inform general drug discovery and can be used by the wider scientific community at the earliest stages of development Drug design and optimization vendors produce algorithms design to improve the drug design process and develop candidates […]
AI in Drug Discovery IV
Companies like Atomwise, Exscientia, InSilico Medicine, Insitro, HealX and Cyclica have been pursuing partnerships with big pharma along with the development of their own compounds. There are two main business models that we’re starting to see here. First, there’s the biotech startups that are using internal research and development to discover new drugs. Second, there’s […]