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Indian Researchers Develop AI and Targeted Cancer Treatment Tools
Scientists in India are working on two ways to improve cancer care.
One project uses artificial intelligence to find rare cancer cells that can cause tumours to return.
These cells can hide among other tumour cells and resist treatment.
The AI tool, called ACSCeND, can study ordinary tumour data and identify different types of stem-like cancer cells.
Researchers found that some tumours with many powerful stem-like cells had worse outcomes.
A second project created a chemical called RK-251 that is mostly inactive outside cancer cells.
It becomes active when it encounters high levels of reactive oxygen species, which are often found inside cancer cells.
Early tests showed that it affected triple-negative breast cancer cells while causing less harm to healthy cells.
More research would be needed to determine how these tools perform in patients.
Researchers developed ACSCeND, an AI framework for identifying three states of cancer stem-like cells.
The framework analyzed more than 25,000 tumour samples from international cancer databases.
Tumours enriched in highly potent stem-like cells were linked to poorer survival, recurrence and weaker immunotherapy response.
Researchers also synthesized RK-251, which activates inside malignant cells with high reactive oxygen species levels.
RK-251 showed activity against triple-negative breast cancer cells and lower toxicity toward non-cancerous cells in laboratory tests.
- Who
- Researchers led by Dr Shubhasis Haldar, Dr Asis Bala and Dr KP Bhabak, with teams from Indian research institutions.
- What
- They developed an AI framework to detect cancer stem-like cells and synthesized a small molecule designed to activate selectively inside malignant cells.
- Where
- The research involved the SN Bose National Centre for Basic Sciences, Ashoka University, IASST-Guwahati and IIT-Guwahati, with analysis of international cancer databases.
- When
- The studies were published on August 24, 2026.
- Why
- The projects aim to address cancer recurrence and the harmful effects of chemotherapy on healthy tissues.
Key facts
- AI framework
- ACSCeND identifies pluripotent-like, multipotent-like and unipotent-like cancer stem-cell states.
- Data analyzed
- More than 25,000 tumour samples from international cancer databases.
- Cancer-cell finding
- Tumours enriched in highly potent pluripotent-like cells were associated with poorer survival, greater recurrence risk and reduced response to modern immunotherapies.
- Drug candidate
- RK-251 remains inactive until it enters a malignant cell and encounters high reactive oxygen species levels.
- Released compound
- RK-251 releases the anti-cancer compound NBDHEX inside cancer cells.
- Laboratory results
- RK-251 was effective against triple-negative breast cancer cells and showed lower toxicity toward non-cancerous cells.
- Additional testing
- Tests in zebrafish embryos showed no observable signs of needless toxicity, while fluorescence helped track drug activation.
Quotes
Researchers behind the ACSCeND study
Researchers from SN Bose National Centre for Basic Sciences and Ashoka University quoted from their NAR Cancer paper
“Defined by their ability to self-renew and differentiate into multiple tumour lineages, CSCs occupy the apex of cellular hierarchies in many cancers”
thehindubusinessline.com
Dr Sivasubramaniam K
Medical oncologist at Prashanth Group of Hospitals
“The two major challenges for modern medicine are relapse or recurrence of cancer cells post treatment, and the side-effects of chemotherapy that destroys normal cells along with cancer cells. AI has the potential to overcome these two challenges. Identifying cancer stem-like cells using AI could predict early relapses. Targeted drugs that become active only in cancer cells and spare normal cells will make a difference to patients. These strategies could be major breakthroughs in modern medicine”
thehindubusinessline.com
Sources
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