Predictions for pharma in 2019
From AI to mHealth, Jim Streeter, global vice president life sciences product strategy Oracle Health Sciences give us his pharma predictions for next year.
1: Pharma, patients & providers come together
The ecosystem of pharma, providers and patients will be tightened and more progress will be made in offering clinical trials as an option for care vs. some elusive option.
2: Cloud-based eClinical systems will infiltrate mid-tier biopharmas
More mid-tier pharmas (David’s of the world) will be leveraging cloud-based eClinical systems for their clinical trial operations to better compete with their (Goliath) competitors. Costly, resource-intensive on-premises technology will begin to be replaced by cloud-based eClinical systems that enable more agility in setting up and conducting clinical trials. Safety reporting for many will be moved to the cloud enabling CROs and Pharmas to access a single source of the truth.
3: mHealth will continue to drive patient-centricity & fewer site visits
More patients will enroll in clinical trials as sites become more flexible in allowing patients to remain at home using mHealth devices to monitor and track their vitals and adverse events. More pharmas will leverage mHealth devices in their clinical trials to increase enrollment numbers while delivering more patient centricity – from wearables for heart rate and blood pressure to electronic diaries for tracking and reporting adverse events. Geography used to stand in the way of patients joining clinical trials. With the help of mobile devices and wearables, patients can remain in the comfort of their own home for most of their clinical trial journey with fewer site visits. And they will once be viewed as the heroes that they are in braving a clinical trial.
4: Artificial Intelligence (AI) will become more mainstream in clinical research, starting with drug safety reporting.
As the sheer volume of data in clinical trials increases, humans will no longer be able to handle it manually, and AI will need to be leveraged to automate some of the work. Safety case management is an area that is leading the way I the adoption of AL. Some of the immediate areas that AI features may be incorporated into pharmacovigilance include: source document processing, case report narrative processing, call center log adverse event flagging, product label processing, literature screening for adverse events, and signal detection.
5: Genetics data and genetic markers will drive precision clinical trials
In 2005, the first genome was mapped and costs millions of dollar. Today, this is common practice. Once we know that a population of people have a certain genetic marker that may have a higher efficacy rate for a drug, we can target that population through providers to recruit future patients for trials. This is where the notion of Clinical Trials as a Care Option comes in. With just a 2% increase in patient enrollment numbers, a pharma can greatly improve the chances of getting the data they need to complete the trial and therefore, a drug to market faster.