Posted on : July 30th 2021
The Coronavirus disease (COVID-19) has triggered a rush of clinical trials to discover vaccines, threatening the continuity and success of non-COVID-19 drug discovery pipelines. This guide will help you learn to mitigate these new challenges, maintain pole position, and grow your business into the future with effective strategies for decentralization.
Defensively mitigating the spread of COVID-19 has helped limit the short-term effects of the virus. However, it hinders the continuation of essential clinical trials to find treatments and cures for many diseases, including the novel coronavirus.
While scientists have rallied together to develop therapies and vaccines for COVID-19, there are other ongoing and scheduled trials in Research and Development (R&D) pipelines that are critical for conquering a host of devastating human diseases. It is immensely important to ensure the continuity of these trials is not interrupted, and that new trials begin on schedule.
There are three critical business considerations to keep in mind as you rethink priorities for clinical trial and drug discovery pipelines in the COVID-19 era:
There are more than 2,850 trials and nearly 900,000 patients enrolled at trial sites in regions that are under partial or full lockdown due to COVID-19 restrictions.1 Partial and complete lockdowns disrupt ongoing clinical trials by barring access to laboratories. Furthermore, organizations report an estimated 25 to 75 percent fall in productivity due to shifting work remotely.1
Research and Development (R&D) teams are analyzing how to stop the knock-on effects of the pandemic — including the increased costs caused by delays, protocol deviations, and trial redesign — from influencing the viability of trial results.
The COVID-19 pandemic has been an inflection point in regulatory affairs for clinical trials. Specifically,
It has brought into focus compliance challenges with frequently changing national guidelines, as well as maintenance of patient safety and the scientific value of research during a global crisis.
Close monitoring of regulatory agencies, investigation sites, health authorities, and competitors is critical for choosing the correct strategy to avoid the penalties of regulatory non-compliance.
The disruption unleashed by the pandemic has accelerated the digital transformation of pharmaceutical companies. The surge to leverage remote patient monitoring, virtual medicine, and Artificial Intelligence (AI) has prompted greater demand for remediating pain points in digital healthcare. These include the urgent needs to tackle any data gaps, identify alternative methods to collect data consistently, and enrich digital education.
Only recently, the pharmaceutical industry has begun incorporating location-independent factors into its drug discovery process.
The pandemic has accelerated a big shift to decentralized clinical trials.
For example, virtual clinical trials have become de rigueur for completing ongoing research, initiating a new drug discovery process, preventing cost overruns, and reducing opportunity costs. There are significant challenges related to information aggregation and extraction, as well as shifting internal resources from transactional tasks to the concentrated achievement of transformational objectives.
There are numerous ways a clinical trial can be made virtual — a decentralized approach to conducting a clinical trial. Some of the more significant methods are: automating clinical data exchange, leveraging offshore resources, using Intelligence Monitoring Systems for news, business intelligence, and research data aggregation, employing digital content to educate and recruit patients, and empowering sales and marketing teams with localized content to elevate study engagement rates.
A clinical study is nothing without data. Before data can be distributed automatically, it needs to be extracted. There are sophisticated AI-based data extraction techniques that can mine information from unstructured data and integrate it into the workflows of various stakeholders. Furthermore, normalization of the extracted data streamlines comparison, analysis, and reporting. Based on commonly used measurement and evaluation methods, manually curated golden datasets can be created. Golden datasets help define what data needs to be gathered and how it will be stored. Consequently, trial evidence is gathered faster and analyzed better, all with more accurately predictable data and processes.
R&D is highly labor-intensive and costly. The continued success of all pharmaceutical companies depends heavily on the ability to innovate around drug therapies and to do so as quickly, affordably, and accurately as possible. Pharmaceutical companies can overcome efficiency challenges by leveraging the computational capabilities and more competitive cost structures in emerging economies that have an ample supply of resources and niche skillsets in chemical, biomedical, and pharmacological areas. Piggybacking on the robust infrastructure and innovative technologies available today, highly complex work such as statistical programming for efficacy analysis, along with low complexity work like safety reporting or data mapping, can be delivered from any geography.
Understanding your competitors’ drug development strategies are important for maximizing R&D investments. However, with today’s heightened competition to uncover a silver bullet for COVID-19 and its attendant regulatory changes, monitoring the scale of drug development pipelines for competitors is not enough. Significantly more granular analyses are vital to an accurate understanding of what is happening broadly in the industry and more specifically, with competitors and regulatory agencies.
Aggregating news, developing competitor profiles, capturing relevant COVID-19 data generated by a multitude of sources, and tracking regulatory changes can be done by deploying Intelligence Monitoring Systems.
To continue running clinical trials and ensuring patient safety, it is necessary to modify protocols, establish new remote procedures, and implement COVID-19 exposure risk-mitigation measures. Beyond the practicalities of protocols and inclusion/exclusion criteria, the human element must be considered; where the ultimate decision to enroll or walk away hinges on resolving a patient’s fears and meeting their aspirations.
By employing digital strategies, patient communication central to this decision-making process can be enhanced in a number of ways. Enrollment can be greatly improved with more competent recruiter communication, which exerts a substantial influence on a patient’s decision to participate. New digital, interactive modules can help sales teams to remain competitive. Teams can also be empowered by offering localized, client-facing assets to achieve better study engagement and patient experience satisfaction.
In summary, the benefits of decentralizing clinical trials add up to the following:
Decentralized pharmaceutical R&D is the present and the future of the drug development process. A well thought out, decentralized clinical trial strategy is vital to the R&D blueprint of every pharmaceutical organization. Significantly, to stay ahead of the competition, pharmaceutical companies must supplement their traditional strengths with new-era skill sets and technologies supported by external experts.
As COVID-19 presents new challenges and opportunities for pharmaceutical companies, adopting the mitigation strategies discussed here will provide R&D teams with an unprecedented capacity to realize cutting-edge, effective, and decentralized clinical trials.
SPi Global’s extensive expertise in content and data extraction, enrichment, and transformation uniquely equips us to be a trusted, guiding partner along your journey. Our suite of leading-edge technology platforms as well as our deep understanding of content workflows and data structures help pharmaceutical companies respond, manage, and lead their R&D successfully during this pandemic and set an innovative course for the future.
Reference 1&2. McKinsey & Co. “COVID-19 implications for life sciences R&D: Recovery and the next normal”. https://www.mckinsey.com/industries/pharmaceuticals-and-medical-products/our-insights/covid-19-implications-for-life-sciences-r-and-d-recovery-and-the-next-normal. Published 13 May 2020.
The process of data extraction involves identifying and recovering alternative and semi-structured data from various data sources such as files, XMLs, JSON, etc.
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