By Pat Jenakanandhini, Chief Product Officer at ArisGlobal
The work of patient safety has never been more publicized than it is today with the development of the COVID-19 vaccines. As you have likely seen, the general public has questioned vaccine safety due to the swift research and development (R&D) process. However, those directly involved in drug development know: technological advancements play a key role in the success and speed of today’s treatments.
Let’s explore some examples of how technology is helping teams bring drugs to market safely and faster than ever before.
Strategic use of automation at the right time
Life sciences is a very risk-averse industry, and rightfully so — there are lives at stake. Make no mistake: as teams work diligently to create new therapies, patient outcomes will always be the top priority. The challenge for many companies is balancing risk and patient outcomes with efficiencies in the research and development process. Today, to solve this challenge, more and more organizations are adopting digital processes such as automation and artificial intelligence (AI).
An example to look at is the system for collecting and analyzing case management data. Before implementing automation, adverse event reporting would need separate teams to submit the data, review it, and create cases in the safety database. Then there are teams in charge of data entry, reassuring for accuracy and assessment, and submission on cases and reporting. This daunting process is slow, expensive, and limits collaboration.
Automation is becoming more advanced every year and can be applied to 50-60% of simple post-marketing cases, or the process of monitoring the safety of drugs once brought to market. There is a lot of hype around generalized automation and AI solutions. However, what really works in advancing drug development is identifying the specific areas where automation tools will bring the most value to speed up mundane procedures. Time is precious, and even more so when life-changing therapies are involved.
As a caveat, I’d like to point out that technology should not replace all of the work humans do, but rather act as a means to help humans do their jobs more effectively. Having real, live safety teams on hand to monitor events, act on adverse findings, and connect with regulators is essential.
Joining electronic data sources and real-world data
Safety case volumes have been rising by 30-50% over the past few years, and that number is only increasing. With so much data to keep track of, there must be a better way to sift through it all. Utilizing a data cloud-powered platform helps teams organize multiple data sources, enable the quick creation of dashboards, and extract data findings faster is an important capability that we are seeing become a reality in automation.
Electronic data sources are more publicly available, including real-world data (RWD). RWD is collected from routine patient healthcare statuses, such as electronic health records or disease registries — all while keeping the privacy of each individual patient secure. Used with a signal solution, it has the power to examine previous trials and results to find insights that can improve the validity of the safety platform.
Gartner estimates that 80% of the top 100 life science companies are already using RWD in some way to support R&D tasks. Just like with automation, while it can improve speed and accuracy, it should not fully replace expert reviewers. Safety data fabric can provide further context to the numbers. With the knowledge graphs developed from RWD, it transforms information into intelligence and wisdom.
Breaking the silos
Life sciences is an interconnected system that cannot afford to be siloed. In fact, data is most valuable when it can be integrated and managed across different domains. This is where technology such as cloud-based safety vigilance platforms allow the smooth flow of data from one team to another.
Cloud-based technology allows for the effective use of a safety enterprise data fabric. This connects safety data to clinical, regulatory, and medical affairs data, as well as any RWD or safety master data. Putting all of this information together into one data fabric creates an invaluable resource and transfers it through the cloud to close the gap between siloed teams.
Interconnecting each data set presents great benefits for life sciences. For example, overlaying medical and safety data enables early detection of safety concerns, and combining safety and clinical trial data amplifies signals that can lead teams to faster trial decisions. It even helps with something as straightforward as improving efficiencies when timely safety data is sent to regulatory teams. Furthermore, while the general public might be skeptical of quick drug and vaccine developments, it’s because technology and improved use of data can bring solutions to the public faster and with more confidence.
Safety first and always
Every technological solution adopted by life sciences has one core inspiration: patient safety. This means keeping patient use and safety in mind, from ensuring a smooth user experience when reporting adverse events to ensure their privacy when analyzing RWD. The life sciences industry has largely been left behind in technological innovations in the past, but as AI and machine learning continue to evolve and drive the safe development of therapies worldwide, the impact for life sciences is palpable and will only get stronger.
About the Author
Pat Jenakanandhini serves as ArisGlobal’s Chief Product Officer, where he oversees all product strategy and management functions. Prior to ArisGlobal, Pat served as Senior Vice President of Products at Accruent and Chief Technology Officer at BlueCielo, acquiring several years of experience building and delivering SaaS products including serving. During his tenure at Accruent, the company completed 5 acquisitions, built a strong product strategy driving growth that eventually led to Accruent being acquired by Fortive, a large publicly listed company. At BlueCielo, Pat was responsible for driving the transformation of the product, the business, and the culture of product & engineering teams to focus on SaaS.
Pat is passionate about building great software that delights users, solves real business problems, and provides a superior user experience. Pat lives just outside Boston, MA with his wife, 2 kids, and a dog. Pat loves building things, home automation, playing video games, and traveling the world. He has an MBA in Finance and dual degrees in Computer Science and Process & Piping Design.