Artificial intelligence is transforming every stage of cancer care—from early detection and diagnosis to therapeutic decision-making and long-term survivorship. As these technologies mature, clinicians who combine frontline medical practice with computational research are playing an increasingly important role in translating innovation into patient care.
Physician-scientist Dr. Latha Kiran Krishna Rajendran is among those working at this intersection. Combining years of clinical experience with research spanning artificial intelligence, computational oncology, immunotherapy, nanomedicine, pharmacogenomics, and predictive medicine, her work reflects the growing convergence of medicine, data science, and precision healthcare.
In this conversation, she discusses how clinical practice inspired her research, the evolving role of artificial intelligence in oncology, and why the future of cancer care depends on integrating technology with compassionate, evidence-based medicine.
Interviewer: Artificial intelligence is rapidly changing healthcare. Why has oncology become one of the most promising fields for AI?
Dr. Latha Kiran Krishna Rajendran: Oncology is uniquely suited for artificial intelligence because cancer is an extraordinarily complex disease. Every patient's cancer has its own biological characteristics, genetic profile, clinical behaviour, and response to treatment. As physicians, we must synthesize enormous amounts of information—including medical imaging, pathology, genomic sequencing, molecular biomarkers, laboratory investigations, treatment history, and clinical observations—to make informed decisions.
Artificial intelligence offers the ability to integrate these diverse datasets into meaningful clinical insights. Rather than replacing physicians, AI has the potential to enhance our clinical reasoning by identifying patterns, recognizing subtle relationships, and generating evidence that supports more precise decision-making.
For me, the true promise of AI is not automation—it's augmentation. The physician remains central to every decision, while intelligent technologies provide additional knowledge that helps us deliver more personalized, evidence-based, and patient-centred care.
Interviewer: Your career bridges clinical medicine and scientific research. How did those two paths become so closely connected?
Dr. Rajendran: They have never been separate. My research grew directly from clinical practice.
Every patient presents a unique story, and every clinical encounter raises new questions. Many of the challenges physicians face don't yet have complete answers, and those unanswered questions naturally became the foundation of my research interests.
Over more than seven years in clinical practice—including primary care, preventive medicine, emergency medicine, women's health, maternal and child healthcare, chronic disease management, and community medicine—I became increasingly interested in how emerging technologies could help clinicians navigate the growing complexity of modern healthcare.
Today, as a General Practitioner and Consultant at Elova Hospitals in Bengaluru, I care for more than 10,000 outpatients annually. Those experiences continually shape my scientific work because they keep my research grounded in real-world clinical needs rather than theoretical questions alone.
Another formative experience was serving as a Medical Officer during India's COVID-19 vaccination programme, where I contributed to administering more than 150,000 vaccinations. Working at that scale highlighted the importance of combining clinical medicine, public health, data analytics, and healthcare systems thinking. It reinforced my belief that the future of medicine lies in predictive, data-driven, and technology-enabled healthcare.
Interviewer: Your research spans immunotherapy, nanomedicine, pharmacogenomics, multi-omics, and artificial intelligence. What connects these diverse areas?
Dr. Rajendran: Precision oncology is inherently multidisciplinary. Cancer cannot be fully understood through a single scientific lens.
Although my research encompasses cancer immunotherapy, CAR-T cell therapy, nanomedicine, theranostics, pharmacogenomics, multi-omics integration, predictive analytics, and machine learning, every project is driven by one overarching objective: understanding cancer more comprehensively so that treatment becomes increasingly individualized.
I've investigated mechanisms of immunotherapy resistance in colorectal cancer liver metastases, explored targeted drug delivery using nanomedicine and the Enhanced Permeability and Retention (EPR) effect, examined theranostic technologies that combine diagnosis with therapy, and studied multi-omics approaches integrating genomic, transcriptomic, proteomic, and molecular data to improve biomarker discovery and therapeutic selection.
Rather than viewing these as separate research domains, I see them as interconnected components of a larger precision medicine ecosystem, where each discipline contributes to a more complete understanding of cancer biology and patient care.
Interviewer: Artificial intelligence is a recurring theme throughout your research. Where do you believe it has the greatest potential to transform oncology?
Dr. Rajendran: Artificial intelligence is most valuable when it helps clinicians interpret complexity.
Modern oncology generates an extraordinary volume of clinical information, and no physician can manually analyse every variable with equal depth. AI allows us to integrate imaging, molecular biology, genomics, pathology, laboratory findings, and clinical data into models capable of generating clinically meaningful predictions.
My research includes machine learning–based clinical decision-support systems for treatment planning, predictive models for Bevacizumab risk stratification, deep learning approaches for survival prediction and adjuvant therapy selection in Stage III non-small cell lung cancer, interpretable machine learning for early mortality prediction in acute myeloid leukemia, symptom-based cancer prediction systems, computational identification of hematological malignancies, and predictive models designed to support earlier cancer detection.
Despite the diversity of these projects, the underlying objective remains the same: developing computational tools that enhance physician decision-making while preserving the central role of clinical expertise, ethical judgment, and individualized patient care.
Interviewer: Your work also focuses on cancer survivorship—an area that is often overlooked. Why is this particularly important?
Dr. Rajendran: One of oncology's greatest successes is that more patients are surviving cancer than ever before. As survival improves, our responsibility extends well beyond treating the disease itself.
Cancer survivorship involves managing the long-term physical, psychological, and social consequences of treatment. My research has explored fertility preservation, cardiovascular complications, renal health, mental well-being, rehabilitation, sexual health, and quality-of-life outcomes among cancer survivors.
Precision medicine should not conclude when treatment ends. It should accompany patients throughout their lives, helping them achieve not only longer survival but also healthier and more fulfilling lives after cancer.
Interviewer: Alongside your publications, you've also pursued innovation through patents. How does innovation complement academic research?
Dr. Rajendran: Scientific research generates knowledge, while innovation explores how that knowledge can ultimately improve patient care.
My innovation work includes artificial intelligence–assisted immunotherapy optimization, intelligent nanocarrier technologies, computational oncology platforms, predictive healthcare systems, and a United States utility patent involving bio-digital twin technologies designed to support precision oncology.
Although many of these technologies remain under continued development, they represent an important step toward translating scientific discovery into practical clinical applications that may help physicians make better decisions and improve patient outcomes.
For me, research and innovation are complementary. One advances scientific understanding, while the other seeks pathways through which that knowledge can eventually benefit patients.
Interviewer: Beyond research, you've authored books, delivered keynote lectures, and spoken at international scientific meetings. Why is scientific communication so important to you?
Dr. Rajendran: Science progresses through collaboration.
Publishing research is only the beginning. Real progress occurs when ideas are openly discussed, critically evaluated, refined, and expanded through collective effort.
Writing books, presenting at international conferences, delivering keynote lectures, and participating in multidisciplinary scientific discussions have allowed me to engage with clinicians, engineers, computational scientists, biologists, and innovators from around the world.
Those interactions frequently generate new perspectives and collaborative opportunities. Many of the most impactful advances in modern medicine emerge when experts from different disciplines combine their knowledge to solve complex healthcare challenges.
Interviewer: Looking ahead, how do you envision the future of oncology over the next decade?
Dr. Rajendran: I believe we are moving toward an era in which artificial intelligence, genomics, molecular biology, computational science, medical imaging, and clinical medicine become fully integrated into a unified precision healthcare ecosystem.
The physician of the future will continue to rely on clinical experience, empathy, and professional judgment while working alongside intelligent technologies capable of analysing complex biomedical information and generating evidence that supports more informed decision-making.
However, technology should never become the focus. Patients must always remain at the centre of healthcare.
Ultimately, the success of artificial intelligence will not be measured by increasingly sophisticated algorithms, but by its ability to diagnose cancer earlier, personalize therapies more accurately, reduce treatment-related toxicity, improve survivorship, and meaningfully enhance the lives of the people we serve.
That vision continues to guide both my clinical practice and my research, and it remains the driving force behind my commitment to advancing precision oncology through responsible innovation.