A single pharmacological project from the bench to the market takes up to 15 years and costs around $$3 billion. Yet, more than 90% of pharmaceutical product trials fail to make it past the clinical stage of development, resulting in significant financial losses.
The cloud has the potential to reduce development time and costs because it gives medical researchers quick access to large volumes of health data, access to
sophisticated data processing tools. As an information sharing and analysis solution tool, the cloud allows researchers to collaborate globally, cutting significant time and costs from the drug development process.
McKinsey article “Cloud’s trillion-dollar prize is up for grabs,” reports that cloud capabilities have the potential to generate value of $100 billion to $170 billion in 2030 for healthcare companies. The major driver of this value lies in enabling researchers to more effectively innovate, collaborate, including new use cases in analytics, IoT, and automation.
Clean, Consistent, Reliable Data
Cloud-based solutions offer decentralized data management and collaborative operating opportunities. Data is stored in one place rather than in silos, ensuring that the data is always consistently reliable. In addition, all data collection processes are initially set up to comply with the Health Insurance Portability and Accountability Act (HIPAA), ensuring proper access clearance to crucial parties. The cloud also provides exceptional transparency, including a clear record of any revisions, retrieval, or updates to the data.
Processing A Million Models in Minutes
One of the key reasons drug developments take so much time is that several hundred genes are involved in inflammatory conditions. Connections between single genes necessitate millions of modeling steps, which leaves scientists grappling with timeconsuming trial-and-error methods. The cloud allows these calculations to be performed much quicker. Cytel’s trial simulation platform SolaraTM, for example, can calculate in fewer than 30 minutes what would have taken 500 hours only a year ago.
Rheumatoid arthritis, for example, is one condition that is very difficult to treat, explains Dr. Zsolt Holló, Head of Center of Biological Business Development and Technology at Egis, a leading pharmaceutical company in Eastern Europe. The company devotes about 50 EUR million yearly to R&D. “During drug development, our major aim is to reduce patients’ experience with ineffective medications. Historically, we’d been using conventional statistical models to analyze correlations between the patient responses and different drugs,” adds Holló. We conducted many modeling attempts, but progress was slow, given the vast number of potential factors involved.”
Egis initiated a Microsoft Azure cloud solution that would allow them to leverage online computational systems to run sophisticated algorithms. Relying on Microsoft Azure, Egis built a more systematic, transcriptome-level approach for response prediction. The cloud-enabled Egis to “try out numerous models fast, to bring results rapidly,” adds Holló. The process, using the Microsoft Azure and the Azure Machine Learning approach, Egis was able to cut the analysis time from several months to weeks and days.
Drug Discovery in the Cloud
The cloud also gives researchers access to sophisticated online data mining tools that allow a faster analysis of large volumes of medical data. This improves accuracy and productivity while giving researchers the ability to analyze historical data to inform their respective clinical research activities.
Scientists and researchers are looking for more opportunities to incorporate advanced data analysis algorithms, artificial intelligence, machine learning, and quantum computing technologies to further assist drug development and biotech research. Is your team trained to handle the data mining potential of the cloud? Get your team cloud-ready with cloud certifications at New Horizons Kingston.