Meet Rita Shaknovich
During medical school, I quickly realized that a propensity to faint in the operating theater was not conducive to a career as a surgeon! Later, during my PhD in molecular biology, I recognized that scientific curiosity was actually my main career motivator – which led me to train as a pathologist and a phsician scientist.
I specialized as a hematopathologist and molecular diagnostician, which coincided with a period of rapid advances in our understanding of the human genome that really inspired my work. My focus shifted more and more towards translational medicine – developing molecular diagnostic tools – that naturally led me from academia to industry.
I was lucky to work for some very transformative companies, focusing on cutting-edge cancer screening, and liquid biopsy testing. A natural progression led me to join Agilent – a global company with a large footprint in healthcare – and I’m super excited to continue advancing molecular diagnostics.
What do you think is missing from the molecular diagnostic toolkit?
The development of cutting-edge technologies in molecular diagnostics has led to incredibly sophisticated tools entering the lab. But we have now reached the stage where the assays are so complex, they can be difficult to implement. So I think the biggest challenge for the instrument manufacturers is simplification of lab workflows.
Our customers tell us that when they buy a new instrument, they want to be able to “plug and play.” Operators need less hands-on time and more automation to relieve workflow burdens. Labs also need the instruments to monitor, maintain, and replenish themselves. In the complex landscape of next-generation sequencing (NGS), manufacturers like Agilent are working hard to provide solutions like Magnis that automate many steps of NGS library preparation.
The other challenge with NGS and other molecular technologies is the complexity of interpretation of the results. There is an urgent need for better tools to assist with analysis of the vast array of genomic variants, and help translate them into clinical action.
And, finally, I think we need to see more research dollars being spent on rare and chronic diseases. While cancer diagnostics are justifiably prioritized, other diseases with genetic origins are equally painful and burdensome. But I do sense that the healthcare industry is starting to shift in that direction, and broaden the lens to focus on overall health.
How do you think precision medicine can be made more equitable in terms of patient access?
Personally I think there is a need for decentralized solutions. Generally, only the large, specialist cancer centers have sophisticated molecular diagnostic tools – the investment of capital and specialist staff is beyond the scope of most hospitals. But that leads to access problems for patients.
I do think it is the responsibility of the diagnostic industries to find ways to decentralize and democratize access to molecular diagnostics. We need to be asking: How can we create more regional solutions? How can the cost and complexity of DNA sequencing be reduced? Can we design mobile units to reach the more remote areas?
Then we need to look at the economics of healthcare. Complexities in reimbursement for molecular diagnostics can be a key impediment to their implementation. We need more government interventions to remove barriers to reimbursement of novel, cutting-edge diagnostics. And we need more pathologists engaging with governments and advocating the value of these technologies.
What's your vision for the future of precision medicine?
Returning to the challenge of simplifying the complex landscape of molecular diagnostics, I think artificial intelligence (AI) and machine learning tools will be transformative in precision medicine.
Our customers tell us that one of the main difficulties with adopting NGS is the translation of a multitude of data points into clinically beneficial action for the patient. I look forward to a future where the combination of molecular pathology experts using AI-augmented interpretive tools will make the technology more accessible. But to achieve it we need to be responsible stewards of the AI.
So my vision is simple: we will become better at delivering precision medicine through the aid of AI and other technologies, and, at the end, the patients will benefit.
To what extent do you think AI-augmented tools will increase the pace of adoption of precision medicine?
Enormously! Let’s look at the example of companion diagnostics (CDx), which could benefit significantly from digital pathology and image analysis capabilities to identify eligible patients for targeted treatments. Interpretation of the results is complex and time-consuming, and CDx manufacturers typically spend a lot of time educating pathologists on biomarker identification, scoring systems, and so on.
However, if we integrate a rigorously trained and validated image analysis software into the pathologist’s workflow, it speeds up the CDx workflow dramatically – especially where there are multiple biomarkers involved. If AI analytics are included as standard, CDx assays that used to be beyond the reach of resource-stretched labs suddenly become accessible.
Which emerging trends or innovations in precision medicine are you most excited about?
In the NGS space, long-read sequencing is a really important development that will continue to enhance the accuracy and sensitivity of the technology. I’m excited about its potential for unlocking further secrets of genetic disease.
I am also a keen advocate for liquid biopsy testing – it makes a huge difference to patients to have the option of a blood test in place of a painful tissue biopsy. The full potential of cell-free DNA diagnostics will only be unlocked when tests have the requisite sensitivity. But, when they do, the patient impact of liquid biopsies for both cancer and chronic disease diagnostics, will be huge.
The other exciting area involves multi-omics approaches for investigating multiple biomarkers. Now that we can perform DNA methylation testing along with proteomics and histone modifications analysis, for example, molecular diagnostics is growing even more powerful than before. There is an emerging trend among diagnostics companies towards combining multiple analytes to understand complex diseases – and I predict we will start seeing the fruits of those labors very soon.
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