"One of the most difficult parts of my job is enrolling patients into studies," says Nicholas Borys, chief medical officer for Lawrenceville, N.J., biotechnology company Celsion, which develops next-generation chemotherapy and immunotherapy agents for liver and ovarian cancers and certain types of brain tumors. Borys estimates that fewer than 10% of cancer patients are enrolled in clinical trials. "If we could get that up to 20% or 30%, we probably could have had several cancers conquered by now." Clinical trials test new drugs, devices, and procedures to determine whether they're safe and effective before they're approved for general use. But the path from study design to approval is long, winding, and expensive.

For the first 125 years of medical imaging, technological advances focused primarily on new modes of imaging as technology progressed from the discovery of the X-ray in 1895 to ultrasounds, MRIs, PET and CT scans in the late 20th century. Now, arguably, the most notable advances are being made in how images from those technologies are securely shared, managed, stored and assessed. These advancements are largely due to the application of artificial intelligence (AI) and machine learning (ML) to imaging systems and data platforms. Automation is improving virtually every stage of the imaging workflow, but there is a lot of hype concerning AI and ML in the marketplace. Companies have underestimated the challenge that complexity presents, and predictions of the end of radiologists have proven false multiple times.

As the COVID-19 pandemic continues to infect people across the world, a technological application already familiar to many in the biotech field is lending a key supporting role in the fight to treat and stop it: artificial intelligence (AI). AI is currently being used by many companies to identify and screen existing drugs that could be repurposed to treat COVID-19, aid clinical trials, sift through trial data, and scour through patient electronic medical records (EMRs). The power of AI in COVID-19 is that it is being used to generate actionable information--some of which would be impossible without AI--much more quickly than before. A simple definition of AI is the ability of a computer to rapidly think and learn. AI utilizes machine learning to analyze large amounts of data.

A poster is seen at the Next forum, which was held by New York-listed Medidata earlier this month in New York. Artificial intelligence is playing a key role in new drug development and smart medical treatment by capturing, analyzing and activating data. It's a category of AI often underestimated by the public, even though it influences the health of millions of people. China, as well as the Asia-Pacific region, is regarded as fertile ground for technology firms working with drug developers, providing artificial intelligence and cloud services. For example, US-based Medidata, the biggest software firm in the life sciences industry, has 357 clients in the Asia Pacific, or about one-third of total client numbers.

In addition to renewing its use of the Medidata Clinical Cloud platform--including key capabilities within Medidata's study conduct and site support suites--Karyopharm is adopting Medidata CSA (Centralized Statistical Analytics) and Medidata TSDV (Targeted Source Document Verification) to enhance its data review process and incorporate modern risk assessment practices into its drug development programs. "As we advance our most promising cancer therapies, it is vital that Karyopharm embraces the latest technologies and evolving trends in the clinical trials space. Adopting Medidata's machine-learning capabilities for centralized monitoring will not only put us in line with the updated ICH E6 R2 guidelines, but will also allow us to view clinical information at a more holistic level, better prioritize trial resources, and maintain data quality and integrity," said Ran Frenkel, chief development operations officer at Karyopharm. "Medidata is more than our technology provider of choice--they are a valued partner that is helping us reach our scientific goals sooner ." A Medidata customer since 2014, Karyopharm has been using Medidata's industry-leading electronic data capture (EDC) and management system, Medidata Rave, as well as integrated capabilities that plug into Rave--including randomization and trial supply management, medical coding, adverse event reporting and clinical trial management--to advance its pipeline of oncology-focused therapies.