Predictive Analytics: The Future of Precision Medicine

Currently, the treatment for cancer comprises of a combination of procedures including surgery, chemotherapy, radiation therapy and immunotherapy. Traditionally, these types of treatments have targeted only the type and size of the cancer. While this approach is currently used across most hospitals globally, it is not necessarily the best one. Recent advancements in clinical research have confirmed that the spread of cancer is caused by genetic changes that occur in a tumor.

This answers an age old perplexing question that doctors have faced for decades about why different people respond differently to cancer treatment. The genetic changes that cause the spread of the disease differ from person to person, even for the same type of cancer. Other rare diseases such as Alzheimer’s disease, multiple sclerosis, and rheumatoid arthritis are also dependent on the genetic makeup of individuals.

Precision Medicine – The Future of Healthcare

 Medical conditions such as diabetes and Polycystic Kidney Disease (PKD) have certain genetic changes linked to them. However, the probability of these diseases occurring in a person is also dependent on non-genetic factors such as diet, exercise habits, quality of the environment and more. Precision medicine allows doctors to account for both genetic and non-genetic factors of the patient’s medical condition and decide on the line of treatment.

Genetic tests will help care providers deliver treatments to patients that their body is more likely to respond to. This saves them from treatments that are less likely to be of any help. Researchers are constantly learning new things about how diseases such as cancer grow and spread by discovering new genetic changes in an affected person. Methods such as biomarker testing and genome sequencing have helped cancer researchers understand genetic mutations so specifically that they now know what kind of condition a patient is suffering from.

 Integrating Predictive Analytics with Precision Medicine

 Predictive analytics give the doctors and researchers of precision medicine an effective tool that helps them save time, costs and money. Clinical trials related to degenerative conditions such as Parkinson’s, Huntington and Alzheimer’s disease can be made both cost-effective and efficient with the use of Predictive Analytics. Techniques such as ‘In silico’ testing have the capability to eventually eliminate the need for animal and human-based clinical trials. This involves the modeling and simulation of clinical outcomes using complex algorithms and statistical models.

CDS systems can now predict patient response accurately by comparing different data classes such as genetic information of an individual and the results from previous outcomes of patients with similar conditions. These immense possibilities are a testament to the power and efficiency of data analytics and predictive modeling. Using a combination of technology and clinical information, researchers can make advancements in precision medicine at a much faster rate.

Data Management

While employing predictive analytics to explore the new frontiers of healthcare and value-based care delivery is a logical step, it cannot happen with a robust data management strategy. The real value of predictive analytics can be harnessed only with the right tools and datasets. Effective means of aggregating data from research settings such as laboratories, clinical trial centers, and EHR systems is the cornerstone of a good data management strategy.

As clinicians and research teams make progress in the laboratory, the need to bring all of these research data under one roof to extract insights from it becomes equally important. Research facilities should consider software solutions with statistical and mathematical modeling capabilities to complement their research. This will not only reduce costs in the long run but also the time taken for breakthroughs that can save lives.


 The efforts of business organizations that can provide a wide variety of solutions having expertise in data modeling, processing, representation, and integration are crucial for the healthcare industry. At Nalashaa, we cater to the needs of research facilities, hospitals and Independent software vendors (ISV) that are looking to shape solutions for precision medicine.

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Amit Manral

Amit Manral

Amit is a healthcare enthusiast who is passionate about the application of creative ideas to improve the healthcare ecosystem. He has been involved with US healthcare for over a decade and loves to understand the challenges of various stakeholders, impact of regulations on them and figure out ways to leverage technology that will impact business positively.

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