AI and chip tech offer real-time view of cancer cells for drug discovery

For decades, scientists have studied cancer cells in petri dishes, but observing them in their living, dynamic state has remained a formidable challenge. Now, an Indian innovator is pairing artificial intelligence with chip technology to change that.

Parmita Mishra, founder of Precigenetics, is developing a platform that combines microfluidics, spectroscopy, and machine learning to watch cancer cells behave in real time. The technology, referred to as 'Ramanomics', could remove a major bottleneck in cell biology: the inability to observe living cells without altering or destroying them.

What is Ramanomics?

Ramanomics is a fusion of Raman spectroscopy and genomics. Raman spectroscopy uses laser light to probe the molecular composition of a sample, offering a non-invasive way to study cells. By integrating this with AI-driven data analysis, Mishra's team can track changes in cancer cells as they respond to drugs or environmental cues.

Unlike traditional methods that require fixing or staining cells, this approach allows researchers to monitor live cells continuously. This could provide unprecedented insights into how tumours evolve and resist treatment.

The chip advantage

At the heart of this innovation is a microfluidic chip that mimics the physiological environment of the body. These chips allow precise control over nutrients, oxygen, and signalling molecules, creating a more realistic setting for cancer research than standard lab dishes.

The chips are paired with sensors that capture Raman spectra at various points, generating vast amounts of data. AI algorithms then interpret these patterns, identifying molecular signatures associated with drug resistance, metastasis, or cell death.

Why this matters for drug discovery

One of the biggest hurdles in drug development is the high failure rate in clinical trials. Many drugs that show promise in static lab models fail in humans because they don't account for the complexity of living systems. Real-time observation could bridge that gap.

By watching how cancer cells respond to compounds over time, researchers could identify promising candidates earlier and rule out ineffective ones faster. This could reduce costs and shorten the timeline for bringing new therapies to patients.

Experts believe this technology could also help personalise treatment. If a patient's tumour cells can be tested on a chip with various drug combinations, doctors could select the most effective regimen without subjecting the patient to unnecessary side effects.

What's next for Precigenetics

Mishra's work is still in its early stages, but the potential is gaining attention. Precigenetics aims to refine the technology further and eventually make it accessible to research laboratories and pharmaceutical companies.

While the company has not disclosed a clear commercial timeline, the scientific community is watching closely. If successful, this could represent a significant step forward in how we study and treat cancer.

As the platform evolves, the focus will be on validating its accuracy and reproducibility in diverse settings. The next few years will reveal whether this real-time window into cancer cells can live up to its promise.