Scientific and medical innovations are continuously evolving with time. With a new decade upon us, not only will drug development be an innovation that will be a focus of medical innovation, but the advent of technologies such as stem cell therapies and biologic adaptations. The research and development path is not as straightforward as one can imagine. The drug development process is a series of combinatorial explosions of possibilities that determine the best path to synthesize a drug. Studies by the consulting firm Deloitte, have indicated that returns on research and development in various biopharma firms is falling. With an average return of 1.9 percent in a 2018 study, the incentive for pharmaceutical companies to want to delve into new ventures will be lessened.
Drug development is a feedback loop, and with time progressions there will be a push for new innovations that are lucrative to emerge in a field that is seeming to decline. The limiting factor to research and development is the cost, and researchers are challenging themselves to bring R&D costs to a controllable level, and maximize the returns on the investments that are attained if a project is to be tackled.
CLINICAL TRIAL OPTIMIZATION
With the current state of the drug development cycles, industry experts have identified that one way to keep innovating and developing products that will be lucrative will be focus on optimization of the clinical trial process. As an interesting design project, clinical trials have standard components that are critical to their success. A deep dive into each of the critical stages will determine where the bottlenecks are. With an identification of the limiting factors, the solution and optimization of the process will be possible. With the advent of the digital age, the transformation process will rely on computing technology to propel the process forward. These digital waves include the internet, which can do things like harness the computing power of computer networks. Social media can assist the research process by facilitating the process of interviewing the target market. Data access via tools like applications (Fitbits and similar technologies) will enable data mining and trend identification. The advent of data access is a disruptive force in the medical industry. Where there is data, there will be the ability for individuals to access critical health trends. From these trends the appropriate solutions in the form of a drug or natural product will be the key to the need.
Once the power of digital technologies is harnessed, the transformation of the drug development process will be facilitated. With the appropriate models, there will be the ability for an organization to forecast various aspects of the drug development process. The disruption of the existing business operating models, will drive the ability for organizations to improve their R&D productivity. The areas of impact will include:
Automation of Processes: With the drug development process, one of the keys to ensuring success in the final stages and even during the pilot stages, is appropriate replication of the manufacturing of the product. Quality management is key to the success of any pharmaceutical product. Process automation is the key to facilitating this outcome.
Data Sets: Data is the new gold. It takes a multitude of steps to synthesize a drug. Thankfully, with the advent of computer technologies, molecular models can be converted into mathematical models, and the pathway for target drugs that will match the desired active sites of their target proteins will be better optimized. Many times during drug development processes, the chemists will synthesize then test, but with the advent of computer simulations, there will be a means via which the mechanism of action and even success can be predetermined, before money is expended on physical synthesis. Predictive analytics is the key to success in the current state of events. The vision will be deciding factor in the drug development process.
The utilization of all of these methodologies will be the key to progress. Optimizing the drug development process via the utilization of Robotic Process Automation as well as Big Data optimization will be the key to reducing the odds of error in the existings research methods. With the advent of Artificial Intelligence, process data at various stages of the process will simply be filtered, processed into suitable process models and then translated into their suitable operating process.
Advanced Statistical Modelling
How does statistical modelling affect you as a patient. More than likely, advanced statistics is a theme that you thought you’d left behind in graduate school. In the medical realm however, as a researcher, advanced statistical models are key to clinical R&D productivity. Statistical models today are centered predominantly around models and simulations, and delves into analytics with methods such as Bayesian techniques. With time, data will be accumulated which can be assessed via these methodologies. Bayesian techniques are applicable even to smaller sample sizes for conditions such as sickle cell anaemia and paediatric studies. Utilizing the appropriate complimentary mathematical tools through each stages of the research, tools such as MCPMod (or Multiple Comparisons & Modelling) can optimize research methodologies and drive critical conclusion.
This article is an introduction to the possibilities that exist in the current statistical modelling methodologies that are helping to change the drug development process. As a start, AI and Big Data will be the key to changing the current state of the decision making process in early stages of the clinical trial. With better decision making, will be better drug development, and the facilitation of successful studies that will be favorable in the sites of regulators.
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