In this interview, Kavitha Lokesh, Vice President of Global Life Sciences R&D Industry Solutions at Cognizant, discusses her role and the impact of precision medicine. With 26 years in IT, primarily at Cognizant, Lokesh leads a global team focused on data analytics, platform implementation, and business operations for life sciences. Precision medicine, also known as personalized medicine, tailors treatments based on individual genetic, lifestyle, and environmental factors, contrasting with the one-size-fits-all approach of traditional medicine. It aims to improve outcomes and minimize side effects through targeted therapies.
Data modernization is crucial for advancing precision medicine, involving upgrades to data systems and governance to ensure efficiency, security, and compliance with standards like SPARE which makes sure data is findable, accessible, interoperable, and reusable. Modernizing data systems supports integrating diverse data types, crucial for patient-centered clinical trials and effective treatment plans. This also includes ensuring data quality, scalability, and robust security controls.
Generative AI is transforming precision medicine by enhancing disease diagnosis, personalizing treatment plans, and accelerating drug discovery. Effective use of AI relies on modernized data systems to handle complex data and automate processes.
Patients play an active role in precision medicine by engaging in their care, contributing comprehensive data, adhering to treatment plans, and using technology to monitor their health. Regulatory compliance and privacy considerations are critical, involving adherence to data privacy laws, securing informed consent, and following international regulations to protect patient data and maintain trust.
Listen or read the transcript below to learn more.
Rebecca Willumson: Hi there. My name's Rebecca Willumson. I'm the publisher of Fierce Biotech, and I'm here today with Kavitha Lokesh, Vice President of the Global Life Sciences R&D Industry Solutions Group at Cognizant. Kavitha, thank you so much for joining me.
Kavitha Lokesh: Thank you, Rebecca, for this opportunity to be speaking with Fierce Pharma on precision medicine today. Looking forward to our conversation.
Rebecca Willumson: So now before we begin, can you tell us a little bit about yourself and your role at Cognizant?
Kavitha Lokesh: Perfect. Overall, I bring around 26 years of experience in information technology, of which 24 years I worked at Cognizant Technology Solutions, predominantly with the life sciences and healthcare customers, focusing in data analytics, products and industry solutions. So currently I lead the Life Sciences R&D Industry Solutions group globally, where we provide services and platform implementation, integration services, data and analytics and business operations support. My team's work today spans the globe across discovery, preclinical, clinical development, as well as in regulatory and safety domain.
Rebecca Willumson: Now tell me, what is precision medicine and how does it differ from traditional medical approaches?
Kavitha Lokesh: Precision medicine is also called as personalized medicine. It's a healthcare approach where you customize the treatment to the individual characteristics of each patient by including their genetic makeup, their environment, as well as lifestyle data. Today it stands in contrast to the traditional medicine's one-size-fits-all approach by including personalization, genetics, as well as more importantly, heavy reliance on data modernization. In fact, I would say making the systems modernized is very crucial for enabling precision medicine.
Also, if you look at from a precision medicine, it often targets therapies that are focused on the molecular mechanism of the disease, potentially leading to better outcomes and fewer side effects when compared to the traditional treatments. So, I would personally believe that precision medicine is a significant shift towards a much more efficient and effective healthcare delivery.
Rebecca Willumson: Now, you mentioned data modernization. Can you elaborate on what data modernization means and why is it so essential for the advancement of precision medicine?
Kavitha Lokesh: It's good that you asked about data. Data is very important to me. My past experience of handling the data and analytics portfolio, I've realized that every event in the universe can be recorded as data, and you can use that data to tell meaningful stories and interesting ones too. So coming to your question on data modernization, it is actually an process of upgrading an organization's data systems and also implementing a robust data governance framework to ensure compliance, security, and most importantly, aligning to core standards, what we call as fair principles, which is basically ensuring the data is findable, accessible, interoperable, and also reusable.
So, data modernization is very crucial when it comes to precision medicine for several reasons. So, let me take an example in the R&D space. The traditional clinical trials generally were drug-centered and the patients were fitted into the trials. But if you take precision medicine, the clinical trials are patient-centric requiring a complete 360 degree view of clinical, molecular, as well as outcomes data about the patient. Now, providing such a 360 degree view really requires robust data integration capabilities, so modernizing your data systems enables us to integrate diverse and multimodal data sets like your omics data, which is your genomics, your proteomics data, your EHR, EMR data, your devices' data, your sensors' data, as well as your images and lab data.
Another important aspect of data modernization is the scalability. So, let me give you a data point of your, as per the Tufts Center for Study for Drug Development, they found that currently phase III clinical trials generate an average of 3.6 million data points, which is almost three times more than what a late stage clinical trials used to generate 10 years back. Now, as the volume of health data grows and the modernized data systems automatically expands to this increase, thereby enabling continuous development in precision medicine. Also, very important is the security because you are handling the patient health data.
So having a robust data ecosystem ensures there are proper security controls to avoid any data breaches. I also touched upon the data governance framework. It is basically implementing policies and procedures in the organization for effective data management. Some of the concepts like data tagging and cataloging of the data as well as the metadata enables faster discovery of the data. Also, lineage of the data is very critical, where you track the entire data journey so that you have proper transparency and also traceability throughout the lifecycle management of the data.
It's also very important in clinical world of audit trails that captures the access to the data and also that records the changes to the data is also very important. So having data modernized systems really helps to ensure that you are able to implement all these components. So in summary, I would say data modernization is key when it comes to precision medicine because it helps the healthcare providers to give personalized treatments with better outcomes. So I would also say the holistic approach that we discussed also ensures that every aspect of data management contributes to the better healthcare outcomes.
Rebecca Willumson: Now, traditional and generative AI have introduced a paradigm shift across life sciences. How is AI impacting the field of precision medicine?
Kavitha Lokesh: I expected this question on AI. Absolutely, AI is transforming every industry and it's no different in precision medicine. I will quote some of the examples where we have seen AI to make an impact. Firstly, we have seen that AI helps in better disease diagnosis because it's able to look at complex medical data, be it your images data or the genetic information, and it's able to diagnose the disease with high speed and accuracy. Secondly, we also seen that AI to play a significant role in defining the personalized treatments because it has the ability to look at the genetic information, lifestyle, medical history data, and also compute and recommend the personalized treatments for the patients. We've also seen AI to accelerate the drug discovery and development. For example, it can predict the protein structure. It also has the ability to tell how a particular compound reacts to the different targets in the body.
And we have also seen that AI's prediction capability when it comes to the disease progression and patient outcomes. We have also seen there that AI plays a significant role. In conclusion, I would say AI is definitely disrupting the industry and as well as the precision medicine. But I would like to lead the statement that any organization looking to scale or execute AI at scale, they really need to focus on data modernization. Because data modernization lays that foundation for data management and produce data products at faster speed that can be then leveraged by the AIML team to really take more benefit out of the data assets that the organization has.
Rebecca Willumson: So tell me, do patients have a role in their own treatments in the context of precision medicine?
Kavitha Lokesh: Absolutely, yeah. Patients play a significant role when it comes to precision medicine. In fact, there are no more passive recipients of care, but more active partners and their involvement is essential for the success of the personalized treatments and also to create a very collaborative experience. So some ways that we have seen the patients to be involved is they have active conversations with their healthcare providers on different treatment options, and also understanding the benefits and the risks associated with these approaches. Also, we have seen that patients contribute more, they're a very comprehensive healthcare information about themselves, be their medical history, their lifestyle, ecosystem data, as well as their genetic information. We've also seen that patients have to adhere to their treatment plans, more importantly, ensuring that they're able to stick to their medication schedules and also ensure that they're visiting any appointments, follow up appointments that they would have.
And more importantly, also make any lifestyle changes so that there is a much better outcome when it comes to their personalized medicine and treatments. Additionally, if you see patients today use their wearable devices as well as their mobile apps to track their health data in real time. So ensuring that they monitor that continuously and report any changes and adverse events to their healthcare providers for timely interventions to their treatment plans is also important. So by keeping themselves informed about their condition and also the latest advancements in precision medicine, I would say patients can make a much more educated decision about their care, empowering them to advocate for themselves and also seek treatments which are much better outcomes.
Rebecca Willumson: So my final question for you today, tell me what are the regulatory compliance and privacy considerations relating to precision medicine?
Kavitha Lokesh: Regulatory compliance and privacy requirements are crucial when it comes to precision medicine because of the patient data that we would be handling. So some of the key considerations would be adherence to privacy laws like HIPAA and GINA in the US, ensuring informed consent from patients and also implementing robust security controls to avoid any data breaches. Ethical concerns related to genetic information and implication of genetic testing need to be addressed within the regulatory frameworks.
Additionally, international standards like GDPR must be followed to ensure cross-border data sharing. Transparency and compliance are two important things when it comes to regulatory and compliance. So this will also require both the healthcare providers as well as the researchers to implement and maintain a clear view of how the data is being used, and also conduct periodic audits for compliance. So these measures are very crucial to ensure the safety of patient data, also uphold ethical standards, and most importantly, maintain the public trust in precision medicine.
Rebecca Willumson: Well, very good, that is a great place to stop. Kavitha, thank you so much for joining me today. I really appreciate the conversation.
Kavitha Lokesh: Thanks, Rebecca, once again for this opportunity to be speaking with Fierce Pharma today.