The profession of genetic counseling has grown exponentially in the past 30 years, considering it only began nearly 50 years ago in the United States. While the service of genetic counseling existed much earlier, the genetic counseling profession reached a global expansion in the early 1990s which in turn led to the transition of being an international allied health profession dealing with inherited genetic conditions, whereas in the past genetic counseling was solely provided as part of medical physicians role. A closer look at genetic counseling:
The National Society of Genetic Counselors in the US (NSGC, 2006) has provided the following definition:
“Genetic counseling is the process of helping people understand and adapt to the medical, psychological, and familial implications of genetic contributions to disease. This process integrates the following: (1) Interpretation of family and medical histories to assess the chance of disease occurrence or recurrence. (2) Education about inheritance, testing, management, prevention, resources, and research. (3) Counseling to promote informed choices and adaptation to the risk or condition.”
Many genetic counselors roles consist of the clinical roles as described in the NSGC definition, however, it has become more common for them to also work in research, industry, education, laboratory, policy, and advocacy positions globally, and the scope of clinical practice will vary both within and between countries.
Utilizing AI technology for the future of comprehensive genomic databases
The (Big) Problem
- Cracking the Genetic Code of Disease
At the very core of most human diseases is genetic code and whether it is in-born genetic errors that can cause rare diseases such as cancer, autism, or genetic pathways that end up affecting biological functions.
- The Unseen Influence
In every human, thousands of genetic variations and errors may affect their overall health and plenty of diseases caused by said variations will remain undiagnosed, or will not manifest until later in adulthood.
- An Interpretation Challenge
The use of next-generation sequencing has become more affordable and available, however, the probability of finding a diagnosis through the use of these technologies is limited by approximately 25% due to the difficulty in identifying the relevance clinically for these genetic variations.
- Limited Data equates to Limited Opportunity
By determining the genetics of a person, clinicians can predict which therapeutic approach would be best for them, yet data linking variations to therapeutic success limits the scope of this precision medicine approach.
The (Big) Solution
- AI Application in Cancer Genomics
The use of AI presents data to and about patients in such a way that humans can interpret it much easier. Using AI to recognise patterns and features leads to the AI making suggestions of course of action based on manmade guidelines.
Ido Rabiner from FDNA Telehealth says that: “Using AI-based techniques to analyse genomic data in large volumes while predicting and suggesting a cause of action is the future of medical genomic technology.”
Using AI in cancer genomics will present multiple benefits like quick and early detection and diagnosis of cancerous cells. The analytics on large scales gives us great insights to the disease. Using AI will help with large amounts of input data leading to better interpretation. AI will also lead to better cancer management by improving personalised treatment plans. It will also better the management of future cancer risks by early detection through AI genetic counseling and testing.
- Genome Sequencing
Using AI in genome sequencing fastens the processing and analysing of sequenced data. It also effectively predicts the genetic alterations associated with rare diseases.
“AI will minimise the efforts and time it takes to effectively develop precision medicine.” says Rabiner.
Algorithms will be designed based on the patterns identified in big amounts of data sets which are in turn translated to models that humans can understand and analyse.
- Medical Workflow optimization
Artificial intelligence betters the process of accessing patient data. This leads to increasing the efficiency in the management of the workflow process within the clinical and medical fields. AI algorithms reduce the time it takes to recognise diseases that need immediate diagnosis and treatment.
- Prophylactic medicine and predictive genomic testing
It is very important to diagnose diseases in childhood. A very standard test being done today is newborn genetic screening. Screening for Down-Syndrome is being done and offered to most pregnant women. AI has the ability to predict the risks as well as the outcomes involved in curing such diseases. This is done through the available data which aids in the performance of gnome analytics of the human body.
- Gene Editing
There are many new technologies that can alter and change DNA sequencing to correct defective genes as well as cure and treat diseases. Within this technology there’s a chance that incorrect procedures lead to mutations during the process. Artificial Intelligence can predict the mutations that could occur during the procedure. This leads to more effective and safe gene editing treatments.
Final take:Thousands of couples may have questions about issues like Down-Syndrome and other genetic issues that can be passed on. The fact that Telehealth has made genetic counseling a reality worldwide, means that there can be more certainty about issues that were previously, mainly uncertain.