More medicines are being developed all the time. The number of new medicines entering the market globally from 2017 through 2021 exceeded the previous five-year period by 47% (link resides outside of ibm.com). And projections indicate further growth through 2026.
As new medicines are developed, even the most extensive clinical trials cannot account for every way that the medicines could interact with individuals and other drugs. That’s why PV is so important. It is the core process for drug safety.
But the information about drugs’ effects in the population — especially after they’ve been released to market — is complex and comes from myriad sources. Before using RPA, Daewoong Pharmaceutical’s PV team conducted a weekly PV process for more than 100 of the company’s products, including medicines for high-risk conditions, such as PRS inhibitors and pulmonary fibrosis treatments, where global data collection is essential to ensuring safety.
The process involved extensive searches — in global and national databases as well as less-structured sources like medical literature and case reports — seeking any data on adverse reactions and events, atypical lab results and more. And the team had to search on every product name as well as the names of each product’s active pharmaceutical ingredients (APIs). Fixed-dose combinations of multiple APIs sometimes require additional searches.
Along with the searches, PV personnel needed to take and save screenshots, download source documents, document search results and upload the data to a Daewoong Pharmaceutical server.
For each one of the 100 products, it normally took one team member a full workday to complete the PV process.
The opportunity for automation was clear, but a first attempt led to flawed results. The PV team used third-party RPA software to automate the search process. The software converted findings into Microsoft Excel spreadsheet data, and incompatibility between Excel and some data sources required manual rework and corrections, delaying reporting and offsetting the efficiency gains from the automation.
Nonetheless, the team knew they were on the right path. They just needed a better solution.