by insights_blog_admin

Despite significant progress in the quality of services offered by health care systems over the last decades, leading to drastic improvements in the health and well-being of the public, our health care systems still, fail millions of people each year. Every patient is extraordinary – his/her genomes, environment, disease history, and exposure to drugs. Tumors are often heterogeneous in their genetic make-up and their response to drugs, both within and between samples. Here is when Genomics comes into action.Sequencing of the transcriptome gives us information on which genes are read out and when, as well as detection of patterns of allelic expression and alternative splicing. DNA sequencing can also be used to characterize the immune system of individual patients, opening the way to make predictive models of the state of the immune system of every individual patient, which is invaluable for diseases with immune components (e.g., type 1 diabetes, rheumatoid arthritis, etc.) or the optimization of immunotherapies for cancer patients.

Revelations driven by genomic information could drastically build the number of biomarkers accessible for use in clinical trials. This information can be utilized to find powerful patient subgroups with genomic profiles that sway security and viability. Yet, while trial sponsors are fusing genomic information in trials, this information is not being utilized ideally. Genomic data can be employed for the following:-

  • Risk assessments
  • Inclusion/exclusion criteria
  • Designing prospective, rather than retrospective studies
  • Actionable discoveries

Genomics has myriad applications in virtual clinical trials within personalized medicine as well as the drug development and discovery pipeline, including:

  1. Early drug development, supporting the pharmaceutical industry and biotech companies in early developmental stages (responder groups can be predicted from public or industry-supplied data and efficiently guide experimental validation in animal or cell line experiments using genomic sequencing)
  2. responder and non-responder groups are identified, enabling a highly cost-efficient, several-fold increase in approval of new drugs.
  3. Drug repositioning, with approval for different disease applications.
  4. Drug rescues (‘fallen angels’), typically for drugs that have failed in phase II or III clinical trials due to low response rates (typically below 20%) rather than due to intolerable after-effects (the identification of responder groups will provide the means of gaining approval for use of these drugs commercially for the benefit of defined patient groups).
  5. Selection of the most efficient drug/drug combination for patients.

Presently assume, you are leading a virtual clinical trial, you have just saved an enormous cost that might have caused during traditional clinical trials like Patient enrollment, Clinical trial administration framework, and issues like Patient maintenance, Site maintenance, Outsourcing expenses, and Site enlistment have additionally been limited.

Amongst the several obstacles, that top the list of issues to watch out for, these five are most commonly encountered:-

1.Small population size: The patient population for a hereditary quality based (change based) trial is more modest than that of a standard infection based clinical trial, as hereditary testing viably bars numerous potential clinical trial members. This is particularly valid for a rare infection trial where the population is less.

2.The patient population might be difficult to recognize. There are a few factors that make understanding recognizable proof troublesome. For some infections, determination is made dependent on clinical discoveries. For these sicknesses, numerous patients have not gone through hereditary testing.

3.Genetic outcomes add a layer of complexity. Clinical trial staff is frequently new to the unpredictability of hereditary transformation information, and they may not precisely decipher hereditary test outcomes. This absence of mastery can bring about irregularities in the manner hereditary data is checked on and utilized for study screening. At last, mistakes in hereditary outcomes understanding can prompt deception being given to patients and families, just as the misidentification or under-recognizable proof of likely contender for trial incorporation.

  1. Comprehensive informed consent is required. There are various public guidelines and principles concerning hereditary testing educated assent, results exposure, and trial investment. Before consenting to test, patients need to completely comprehend what’s included and how their hereditary data could be utilized.
  2. Without ceaseless commitment, patients can lose interest. The course of events from persistent enlistment, screening, characteristic history study enlistment, and interventional trial support can be long. Without an arrangement for routinely captivating patients, trial support may discover its members lose interest before the clinical trial even starts. This may make people pull out of the examination or conceivably look for an alternate trial that is on a quicker timetable.

Although the above-mentioned challenges are present in most genetics-based virtual clinical trials, they are not insurmountable. To gain community physician support, programs must be put in place to enable effective screening by physicians in their clinics or in-patient homes. Then, only the patients who meet inclusion criteria are referred to the academic medical center for an on-site evaluation. This allows community physicians to retain stewardship of most of their patients, which can encourage physician buy-in and support. Clinical trial staff is in some cases lacking in genetics knowledge. It is useful to perform a comprehensive skills evaluation to get a sense of these differences. Once, the potential shortcomings are known, one can work towards resolving them. This may include drawing specific protocols for the processing and analysis of genetic data; providing staff with additional training and education on genetics and how to interpret test results; stretching trial timelines to ensure in-depth review and quality spot-checking. To prevent mistakes that can lead to misidentification issues, organizations should also consider regularly auditing the analysis of genetic test results. To maintain enthusiasm and interest for the trial, it is important to bridge the time between when a patient is identified as a candidate and when the trial begins.

There is a need for comprehensive patient education and daily contact here, so patients know what the findings of the genetic test mean and what their choices are. At this time, trial sponsors can also discuss solutions for family members who have the same disorder or who share the risk for it.

To a clinical trial, a genetic aspect adds several complexities. Strategic thinking and adequate skills and resources are needed for patient recognition and engagement. For clinical trial workers, genetic findings may also be difficult to decode.A trial sponsor increases the possibility of trial success by identifying these possible pitfalls and being diligent about fixing them and can gain stronger and more impactful perspectives from the research.


  1. https://www.karger.com/Article/PDF/441553
  2. https://www.medidata.com/en/blog/genomics-data-transformative-clinical-trials
  3. https://www2.deloitte.com/content/dam/insights/us/articles/22934_intelligent-clinical-trials/DI_Intelligent-clinical-trials.pdf
  4. https://www.melbournebioinformatics.org.au/project/gvl/
  5. https://www.nature.com/articles/s41576-020-0272-6


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