The Biggest Changes to Pharma of 2020 & How Technology Will Help in 2021
February 12, 2021, 5 minute read
Let’s face it, as I write this in early February of 2021, the pandemic continues to change the healthcare and life sciences industry. I expect that this year, we will witness a continued breakneck pace of change. The infamous J.P. Morgan Healthcare Conference in early January tried to address some of these changes, and I want to distill a few takeaways from it for you. What big changes have occurred? How are enabling technologies providing paths forward? Let’s jump into it.
What has changed in Pharma recently?
Clearly, COVID-19 awakened the scientists and business model innovators. The industry has dynamically responded to challenges in times of human need. The response highlighted excellence in global business development, discovery pipeline and portfolio readiness, supply chain agility, and clinical trial support. It was notable how the most agile and dynamic companies came up with game-changing solutions, and how an ecosystem of partners could help plug games to execute across an enterprise. Kudos to colleagues who worked tirelessly to align needs and solutions, especially colleagues conducting portfolio strategy, artificial intelligence, and process optimization. However, I think we will continue to uncover massive gaps in commercial operations, regulatory affairs, medical affairs, pharmacovigilance, and patient engagement. In addition, we see how there are many inconsistencies across global innovation, manufacturing, and distribution – and where multinational competition is facing dynamism and innovation from relatively new Indian and Chinese corporations and collaborators.
5 relatively new challenges Pharma will respond to through technology:
Due to the breakneck pace of innovation, people are worried that new drugs haven’t undergone the same rigor and risk mitigation. To keep pace, but have the ability to manage risk, Pharma must modernize Pharmacovigilance. Requirements to report events will get more stringent, while global event adjudication, aggregation, deidentification of data becomes ever more complex and necessary. In addition, with so many new patient touchpoints – from forums and chatbots to social media – it is the responsibility and opportunity for top Life Sciences companies to listen, understand, seek truth, and manage brands through data collection, analytics, and machine learning.
I’m looking forward to an integrated patient diagnostic and drug treatment that hits the market at the same time. Further cytogenetic understanding, biomarkers, and companion diagnostics will have to hit a new stride. It looks like the last couple decades of investments in flexible drug platforms (e.g. RNA), discovery pipelines, and cytogenetic profiling are starting to pay off. Alignment of basic research and development processes will completely change – something that Natural Language Processing and scraping of unstructured textual documents could help with.
We know that COVID-19 demonstrated the need for Supply Chain orchestration and resilience through localization, collaboration, partnering, and M&A activity. Technology will also disrupt more traditional areas of Pharma – industrial internet of things will make dynamic production and logistics much more data-driven and traceable. Reducing bottlenecks, stockouts, waste, and efficiency measures will become more present as the cost of goods sold and capital investment in new drugs is projected to rise as a percentage of revenues.
Patient engagement is changing. The modern consumer expects much more direct contact with the producer of their products. Forward-thinking companies – from Delta’s twitter & flight operations link, to virtually any company with an Instagram-first brand strategy – are able to direct traffic from the control tower. Social listening, chatbots, and mobile strategies to engage will generate new interactions. Pharma can centralize, map, and comprehend their engagement touchpoints by using NLP platforms and toolkits.
Medical affairs will take on more responsibility as the single source of truth for regulatory and medical engagement. In particular, Medical Affairs will have to more closely partner with IT in order to implement data centers, research analytics, and upgraded communications processes. There’s a current push to digitize medical touchpoints, address shifting stakeholders, and partnering with Hospital Pharmaceutical Selection Committees. I think that, in addition, the medical affairs function will become a digital librarian and machine learning manager to liaise between R&D and commercial operations. Technologies such as natural language processing and machine learning platforms will help make quick work of the mountains of paperwork and interactions.
Certain service providers will help pave the way towards better solutions.
This could include Clinical Trial Management Systems, Study builders and adjudication tools, patient clinical trial matching and referral engines, medical record staging platforms, and more. But add to these systems machine learning, natural language processing, and robust automations, and you will have a roadmap for the next couple of years.