The Covid-19 pandemic has impacted every facet of our society — how we work, live, learn, and play — and normalcy will not return until we find a proven vaccine. While multiple pharmaceutical and biotech companies have raced to develop a cure, a viable vaccine might still be a year out.
While we’re searching for a cure, the Covid-19 vaccine race has opened up a broader conversation about drug discovery and how we can leverage our technology resources to accelerate it. Covid-19 came on suddenly and without warning, and global epidemics are becoming more frequent, coinciding with factors like urbanization and climate change.
Technology companies have a role to help accelerate a path to discovery by providing pharmaceutical and biotech organizations with agile, cost-effective, and secure tools. Here are three ways modern technology can impact new roads to drug discovery.
Flexible cloud computing offerings to enable collaboration and flexibility
Before the Covid-19 pandemic, healthcare organizations worldwide faced pressure to drive digital transformation and meet increasing patient demands. This transformation begins with rethinking cloud infrastructure, and it’s clear there is a cloud migration happening. Now, in the midst of Covid-19, adopting cloud infrastructure takes on an entirely new significance. When it comes to drug discovery, the healthcare industry can look to the cloud as a way to accelerate, collaborate on, and drive clinical trials. Moderna, an mRNA technology platform, for example, leverages a cloud-based computational system to run various algorithms and work to improve how medicines are both discovered and developed.
Scientists and clinical specialists from around the world can access data (with appropriate credentials) and use their time engaging in scientific studies, rather than figuring out how to get the files back and forth. The cloud also offers organizations the ability to add compute and storage capacity without taking resources away from other projects. With an event as fluid as Covid-19, no one planned for the computing infrastructure, and companies had to adjust quickly.
Artificial intelligence and big data analytics to fast-track analysis
In healthcare, leveraging data efficiently and speeding time to insight can make or break the difference between finding a cure or failing a drug approval. With clinical trials, for instance, the speed of collecting, processing, and analyzing data is paramount because data integrity is critical – the information must be relevant, non-redundant and accurate for the given trial or study at hand. AI allows for applications and tools to quickly perform this analysis in minutes, compared to what would have typically taken humans weeks or even months. Trials will still require time for doctors and scientists to deliver the drugs, observe the results and compile conclusions, but the time saved during the computational component with AI could help to reduce the overall lengthy data analysis process and ultimately save lives.
Outside of the computational component, delivering data to the various entities involved in drug discovery in the format each entity expects or requires is another challenge that can be addressed with AI. By deploying pre-set algorithms, results can be sent to patients, pharmacists, scientists, the drug registry and also to anonymized research databases, in the format that is appropriate for each recipient — for instance, HL7 for the patient record, text for the drug registry, coded tables for the scientists, etc.
We can also consider the impact of big data analytics on human genome mapping, which can be used to personalize patient care based on data on disease conditions, statistical differences, etc. AI helps to automate searches through massive amounts of data to develop and recognize patterns that can be attributed to each person, each disease and each drug. Based on recognized patterns, models could predict a patient’s chances of developing a disease or response to different treatment options. Treatment plans can then be developed, recorded, tracked and re-inputted back into the databases. This intelligent approach to personalized medicine has been promising and will continue to improve.
Resilient, secure IT infrastructure
Security and compliance are extremely important within the healthcare sector given the sensitivity of dealing with patient data, as well as the need to keep proprietary technology safe. Therefore, security plays a big role in determining modernization of technology and cloud deployment decisions.
Drug discovery can’t happen without collaboration, but collaborating in the medical field is complex. Along with protecting patient data, each company involved in medical studies and trials has competitive intellectual property to protect. Understanding the specific security features of each technology is critical to protecting patient data and keeping intellectual assets safe. As this article suggests, the stakes are especially high in the pharmaceutical industry to protect personal medical information and data, and the same security measures apply to vaccine research. Hybrid cloud might be the best option for healthcare companies, but regardless of the infrastructure chosen, security and compliance must remain top priority.
Inefficiencies, complexity, and costs of traditional IT infrastructures can create roadblocks to the life-saving goals of the healthcare industry. As this industry progresses down the digital transformation path, secure, flexible cloud technology, AI and data analytics will enable pharmaceutical and biotech companies to collaborate in creating new treatment options for diseases and hopefully, effective vaccines for Covid-19. The technology runs hard in the background so the scientists can focus on the important, patient-facing work. IT teams must continue to provide solutions that are efficient, easy-to-use and cost-effective.
Photo: Blue Planet Studio, Getty Images
