For research organizations to survive, thrive and deliver on their missions, they must fully embrace new processes and vital technologies enabling transformation.
Patients and society have never relied more heavily on scientific discovery and medical evidence development. The same challenges driving these needs have disrupted the existing research system, which was already facing significant signs of strain and need for modernization.
Heavily manual workflows, reliance on in-person interaction and outdated methods of data management are unscalable solutions. Overcoming resource, collaboration and funding constraints requires the adoption of new paradigms. Leveraging the latest digital and data science tools is critical to restoring and accelerating the “bench to breakthrough to bedside” care delivery journey.
Augmenting scientists’ ability to identify novel correlations, potential targets and candidate molecules requires the best that modern data science has to offer. Careful data aggregation and governance are crucial.
Critical tools that effectively and rapidly analyze data are vital. Natural language processing (NLP), artificial intelligence (AI), machine learning (ML), and deep learning (DL) all power efforts such as outcome modeling, protein folding, genomics, proteomics, microbiomics and other emerging methods.
High-performance computing (HPC) is needed to accelerate the understanding of candidate targets and the characteristics and behavior of molecules. Researchers are using AI/ML simulation models to study areas including pharmacokinetics, toxicity, bioavailability and potential interactions.
Research can further be augmented to compelling advantage through AI-driven computer vision applied to cryogenic electron microscopy (CEM), digitized pathology and clinical imaging.
Enable workflow automation by coupling next-generation networks with IoT sensors and AI-driven computer vision. Collect and process data from research tools like smart cameras and lab instruments faster.
These technologies not only enhance the richness, quality, accuracy and precision of critical measurements, but they accelerate the transformation of your data into actionable insights.
The pandemic has disrupted or canceled many clinical trials globally and highlighted the limitations of the industry's decades-old methodologies. Research must progress beyond processes centered on periodic in-person checkups and data collection.
The path forward is powered by modern digital applications, optimized televideo collaboration tools and IoT-powered remote patient monitoring coupled with real-time analytics. This transformation will improve safety, increase engagement and provide richer, more meaningful data for clinicians and patients alike.