Pharma and Biotech Companies are Counting on Cloud Computing and AI to Help Accelerate Drug Discovery

April 28, 2020 | min

The COVID-19 pandemic has impacted many facets of our society—how we work, live, learn, and play. While we live in an unprecedented time that is going to have far-reaching societal changes for the foreseeable future, we as the human race will have to continue to forge ahead. Normalcy will not return until there is a proven vaccine. Multiple pharma and biotech companies around the globe are racing to fast-track the COVID-19 vaccine, which still may be at least nine to 12 months away. In fact, as of today, there are about 70 COVID-19 clinical trials underway. While COVID-19 is the current focus for the majority of the scientific community, the bigger question is: how do we leverage technology to accelerate drug discovery in general? 

As healthcare undergoes digital transformation to improve patient outcomes, it is easy to get lost in seemingly limitless possibilities when it comes to disease eradication, preventive care, healthcare delivery, and various treatment options. Next-generation technologies, such as artificial intelligence (AI) and machine learning, promise to enhance the way we live as we unlock the power of both human and health data. The livelihood of businesses in the pharma space revolves around shortening the drug discovery cycle and in the process, lowering the overall investment to bring new drugs to the market. The speed and success of collecting, processing, and analyzing high-quality data is of paramount importance in any clinical trial (one of the main reasons why it will take several months before we can understand the efficacy of the on-going COVID-19 clinical trials). Whether sequencing the human genome, researching new drugs, or conducting clinical trials, the right data can unlock the key to enriching the future.

IT plays a pivotal role in the era where collecting and analyzing data could make or break the organization. IT is this essential group that must be able to deliver the right technology stack, services, and enablement to leverage the value of data in the desired way. But inefficiencies, complexity, and costs associated with traditional IT infrastructures are creating frequent roadblocks that inhibit companies from achieving their life-altering goals. Pharma and biotech organizations are exploring new and improved methods to deliver IT services in an agile, cost-effective, and secure manner. Improved availability of analytics and real-time data processing are some of the keys to accelerate drug discovery.

Embracing the cloud for improved collaboration and accessibility

While pharma organizations have been slow to adopt modern technologies such as cloud computing due to compliance and regulatory concerns, the need for improved collaboration and data sharing gives them no other alternative than to embrace the change. According to ESG research, 65% of healthcare organizations will increase technology spend on public cloud infrastructure services over the next 12-18 months. Additionally, when it comes to datacenter modernization, 20% of pharma organizations will make the most significant investment in implementing hybrid cloud management software. Some of the leading pharma organizations are now leveraging cloud platforms across geographically dispersed R&D teams to collaborate and drive clinical trials. Moderna is one such company that is using a cloud-based computational platform to run various algorithms to design each mRNA (messenger Ribonucleic acid) sequence. 

Artificial Intelligence can fast-track data analysis

Data is one of the most critical elements in the pharma space, which can make or break business.  Value-based decision-making, the speed at which an insight can be derived, and the time it takes to implement or act on that insight can make the difference between curing cancer and failing an FDA drug approval. Hence, for companies to achieve success and derive essential insights, they must make effective use of data analytics tools and technologies. Using data visualization, modern pharma companies recognize the importance of efficiently communicating insights or sharing results with patients. 

Whether a company is conducting drug trials (pre-clinical or phase 1/2/3) and needs to share data with a patient based on individual results or is highlighting ways various medications or treatments affect certain areas of the body, timely access to properly visualized data has a direct impact on patient satisfaction. For example, computational drug discovery uses a combination of cloud computing and artificial intelligence to make the drug development process faster and cheaper. The big drug companies are taking advantage of improvements in AI and the computational power of the cloud to test this new approach. Pharma companies are using this tech-driven process to develop traditional medications as well as completely new categories that work at the level of DNA and RNA to stop disease.

Big data analytics in genomics

Advancements in technology and the decreased cost of computer processing and storage have allowed human genome mapping businesses to thrive, enabling them to harness large data sets of structured and unstructured data to gain meaningful and actionable insights. Genomic businesses can better personalize medicine based on processing data that examines disease conditions, available sets of normal genes, and statistical differences ascertained upon seeing the interaction of the two. What’s more, AI is being used to identify patterns within genetic data sets. Based on those recognized patterns, AI models may be able to predict a patient’s chances of developing a disease or determine the patient’s response to various types of intervention and treatments.

For pharma and biotech companies, the speed at which value can be found in data is paramount to success. Data must be accessed, processed, and analyzed quickly. Efficient business processes must be in place to ensure insights gained can be quickly made available and applied to the relevant areas of the business. As organizations in this space progress down the digital transformation path, it’s more important than ever for data to be properly stored, controlled, and secured to ensure compliance. This is especially crucial as new technologies are added to an already complex data pipeline, including big data processing, advanced analytics, and machine learning. 

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