Physicians, including pathologists, will be able to see a more holistic picture of the mechanisms of disease using sophisticated computer-generated models
Medical diagnosis and treatment will be greatly influenced by the fast-growing field of computational medicine. It is a development with the potential to significantly change how physicians use clinical laboratory tests and anatomic pathology services.
Computational medicine describes how researchers are using sophisticated software tools to map highly complex biophysical and disease pathways. This cutting-edge imaging technology enhances their ability to decipher the complex, often non-intuitive dynamics of human disease.
Produces a More Holistic Picture of Disease
Computational medicine is arriving, a blog post at Scientific American stated. “The field has exploded,” declared Raimond L. Winslow, Ph. D., Director, Institute for Computational Science, Johns Hopkins University Whiting School of Engineering and School of Medicine. Winslow is one of four professors at Johns Hopkins University co-authored a review of the fast-growing field. The journal Science Translational Medicine published the paper in its October 31 issue.
Computational medicine brings together methods from engineering, mathematics, and computational science. It is the natural progression of more powerful computing, better modeling programs, and a flood of raw biomedical data.
“Statistical learning is applied to high-dimensional biomolecular data to create models that describe relationships between molecules and networks,” stated the JHU authors in the paper abstract. “Computational medicine can help you see how the pieces of the puzzle fit together to give a more holistic picture.”
The new modeling helps scientists understand the mechanisms of disease and complex biological processes. These intricate interactions can involve feed-forward and feedback loops, as well as crosstalk on cellular, molecular and genetic levels. This is where advances in computational medicine promise to make a large contribution, according to the Scientific American.
Computational medicine also aids in diagnosis and in testing the effectiveness of different therapies. An article published at JHU’s news website, the HUB, noted further that computational medicine allows researchers to: better understand how networks of molecules are implicated in cancer and predict which patients are at risk of developing the disease; look at how biological systems change over time from a healthy to an unhealthy state; and detect changes in the shape of various structures, such as the brain.
In their paper, Winslow and his colleagues gave examples of how computational medicine has been applied in the fields of cancer, diabetes, cardiology, and neurology. They also described both advances and challenges in translating these computational methods to clinical use.
Cross-trained Physicians Bring New Perspective to Medical Diagnosis
“Our intent in writing this journal article was to open the eyes of physicians and medical researchers who are unfamiliar with the field,” stated Winslow in a story published at Laboratory Equipment. “There is a whole new community of people being trained in mathematics, computer science, and engineering, and they are being cross-trained in biology,” he exclaimed. “This allows them to bring a whole new perspective to medical diagnosis and treatment.”
These new models will soon be translated back to individual patients, the Scientific American blogger stated.
According to Winslow, computational medicine is indeed already under way. One example is a new iPad application that uses computational anatomy methods. It guides doctors in delivering deep brain stimulation to patients with Parkinson’s disease.
“We are poised at an exciting moment in medicine,” Winslow wrote. “Computational medicine will continue to grow as a discipline because it is providing a new quantitative approach to understanding, detecting, and treating disease at the level of the individual.”
As it reaches maturity and is cleared for clinical use, computational medicine promises to give physicians richer guidance on how to identify the patient’s symptoms, then order the appropriate medical laboratory tests and/or anatomic pathology services. In this regard, computational medicine is likely to play an important role in developing new evidence-based medicine guidelines.
In turn, these evidence-based guidelines are likely to direct physicians to use more complex clinical lab tests―such as multiplex assays―in order to diagnosis disease earlier and more accurately. This will create new opportunities for medical laboratories and pathology groups to deliver more value to physicians and their patients.