Emerging technological advances in the field of Hematological malignancies

Oncology is one of the most rapidly evolving frontiers of medicine today with exciting recent technological advances like next-generation sequencing, targeted drug therapy, and emerging role of Artificial Intelligence (AI), among others, pushing the boundaries of cancer therapeutics. Blood as an organ is extremely resilient and transplantable and that gives researchers and clinicians the incredible flexibility in testing its limits and designing novel strategies with the ultimate goal of cancer cure. Hematopoietic disorders are often driven by genetic mutations and alterations.

The 2016 revision of the WHO classification of tumours of haematopoietic and lymphoid tissues increased the number of disease entities whose diagnosis was strongly supported by a specific genetic change. Combinations of mutations rather than individual lesions are being used to classify heterogeneous disorders and direct treatment. Furthermore, the role of different genetic aberrations as markers of measurable residual disease is being evaluated in clinical trials to allow intensification/de-intensification of treatment as appropriate and early detection of relapse.

As we make our way through the 21st century, technology continues to rapidly evolve. The role of genetics in health care is starting to change profoundly and a new era of genomic medicine is upon us. Genomic medicine is the study of our genes (DNA) and their interaction with our health. Genomics investigates how a person’s biological information can be used to improve their clinical care and health outcomes through effective diagnosis and personalised treatment.

Early diagnosis of a disease can significantly increase the chances of successful treatment, and genomics can detect a disease long before symptoms present themselves. Genome-based research is already enabling medical researchers to develop improved diagnostics, more effective therapeutic strategies and better decision-making tools for patients.

Ultimately, it appears inevitable that treatments will be tailored to a patient’s particular genomic makeup. NGS (next generation DNA sequencing) technologies have resulted in mapping of the human genome and have thereby providing the blueprint to understanding how genetic changes lead to disease. In the past, the size and complexity of the human genome was a major obstacle for the sequencing of human cancer genomes.

The development of NGS technologies has revolutionized our ability to analyze cancer genomes, as massive parallel sequencing leads to the simultaneous generation of millions of short DNA sequences. Those sequences are then mapped back to the human reference genome, ultimately creating a picture of the cancer genome. With regard to cancer studies, sequencing both the tumor and the normal tissue from patients is crucial. One must compare a tumor genome with its paired normal genome in order to appropriately identify acquired sequence variants.

The fundamental premise of cancer genomics is that cancer is caused by acquired mutations, and consequently it is a disease of the genome. With the advent of NGS, cancer genomes can now be systemically studied with several ongoing large scale cancer genome projects around the world. Individual cancer sequencing may, therefore, provide the basis of personalised cancer management.

The main disadvantage of NGS in the clinical setting is putting in place the required infrastructure and also the personnel expertise required comprehensively analysing and interpreting the subsequent data. The introduction of NGS technologies allows for the analysis of genomic and providing new insights into haematological malignancies.

Emerging evidence indicates that genomic data can be useful for diagnosis, prognosis and prediction of response to specific treatments, as well as in the development of novel targeted treatments for patients with hematological disorders.

Another breakthrough is the advent of AI in a field of healthcare. AI in medicine refers to the use of AI technology/automated processes in the diagnosis and treatment of patients who require care.
There is an increasing interest in the applications of AI in healthcare to improve disease diagnosis, management, and the development of effective therapies. Given the large number of patients diagnosed with cancer and significant amount of data generated during cancer treatment, there is a specific interest in the application of AI to improve oncologic care.

AI can quickly understand how cancer cells become resistant to cancer drugs by learning and analyzing data on large drug-resistant cancer trials, which can help improve drug development and adjust drug use.

This can provide important insights and information that cannot be found by human identification, and personalize treatment for each cancer patient. AI could speed up the discovery of new materials, a move that could dramatically accelerate the development of anticancer drugs. It has been estimated that a physicians and oncologist need to read several hours a day in order to be updated about new medical research.

Moreover, every year, the medical literature increases by doubling the amount of information. Integration of AI technology in cancer care can provide a way to integrate the current knowledge and give to our patients the best possible care. It can improve the accuracy and speed of diagnosis and aid in clinical decision-making.

While there is a sense of great potential in the application of AI in medicine, there are also concerns around the loss of the human touch in such an essential and people-focused profession. Therefore, the idea is not to excessively over-automate the medical and health care fields, but to sensibly identify those areas where automation could free up time and effort. The goal is a balance between the effective use of technology and AI and the human strengths and judgment of medical professionals.

The application of genomics and AI is going to continue to evolve and have a greater impact on diagnosis and management of haematological malignancies. In the next few years we will see an explosion of knowledge in this area and the application of that knowledge and lead to better health outcomes.