Changes in healthcare practices are a fundamental part of social and intellectual evolution. 

Given the explosion of data generation in the life sciences, and the extension of the industry’s end-to-end supply chains it is crucial that we employ solutions for global and social collaboration. Intelligent information processing and analytics, experimentation and modelling, simulation and calibration are technologies necessary to tackle today’s and tomorrow’s drug discovery and development challenges. These solutions should allow the healthcare industries to rethink their value chain, which will ultimately benefit patients.

Physical 3D modelling is used to produce precise representations of patients’ anatomies. This enables medical teams to plan and rehearse complex surgeries, and to produce life-saving implants and prostheses tailor-made for individual patients. It’s a remarkable evolution that is already having a tremendous impact on patient’s lives.

However, this is only the tip of the iceberg. The true revolution in medicine and medical care in the 21st century will not come from such physical models, but from virtual ones. One day, these virtual models will be able to simulate the true physiology and pathophysiology of human beings – even an individual patient – changing forever the way we research, diagnose and treat injuries and disease.

While your virtual twin may seem like a distant dream, progress in bringing this dream to life is actually already well underway in the nascent field of Biointelligence. BioIntelligence uses computer technologies to model, simulate, visualize and experience biological medical processes in a virtual environment.

While drug makers have for some time modelled and screened virtual proteins and compounds against medical databases, drug development and production remain largely rooted in the real world, and collaboration between disciplines and organizations has been limited.

Every day, drug makers work to produce real drugs that they test on real animals, and then on real patients in real clinical trials. And the time and money they expend is staggering. According to Tufts Center for the Study of Drug Development drug makers today can expect to spend $2.9 billion over ten years to bring a single new drug to market

Add to this challenge the dynamism and complexity of living systems, and it becomes clear that a collaborative approach to research and development, along with the use of virtual modelling and simulation, could bring enormous benefits to life science and healthcare industries.

Collaboration between scientific disciplines and between pharmaceutical companies, research labs, health service providers and computer companies would allow sharing of knowledge and experience to foster insight and innovation.

And, the collaborative use of computer models and simulation would enable researchers to better understand complex systems and more accurately predict the biological effects of various medicines and treatments, enabling drug makers in turn to fine tune real-world assays and eliminate ineffective treatments from trials before the drugs are even produced.

The changing landscape of research today is forcing the bioinformatics community to seek a new level of data sharing and collaboration only made possible with new platforms.

Such approaches could also open the door to truly personalised healthcare medicine as collaboratively produced models and simulations are combined with real world data from individual patients. These changes could produce significant innovation and gains in efficiency, effectiveness and safety, bringing better heath treatment outcomes to everyone.