Can quantum computing help researchers identify promising new treatments for colorectal cancer?
That’s what University of Colorado Cancer Center members Daniel LaBarbera, PhD, of CU Anschutz, and Karolin Luger, PhD, of CU Boulder, are looking to find out in a new study funded by an AB Nexus grant — a university-funded initiative to encourage and expand multidisciplinary research collaborations between the CU Anschutz and Boulder campuses.
“Colorectal cancer is one of the more prominent cancers diagnosed worldwide every year,” says LaBarbera, director of the CU Center for Drug Discovery in the Skaggs School of Pharmacy and Pharmaceutical Sciences. “We’re trying to develop next-generation precision oncology drugs that will be more effective but also synergize with standard of care chemotherapy.”
Going quantum
To achieve this, LaBarbera, Luger, and their team are working with the quantum computing company IQM Quantum Computers to use a quantum computer — an atom-based computer that is exponentially faster than a traditional computer — to identify chemical compounds that might be effective at treating colorectal cancer and inhibiting resistance to chemotherapy. The researchers will educate the computer by showing it compounds they have already found to be promising candidates, then feed it a library of 36 billion potential compounds to evaluate.
“The AI algorithms will take these molecules, break them down into fragments, and then reassemble them into potential drugs, and we're going to try to optimize their drug-like properties in the process,” LaBarbera says. “When it tells us which molecules have the best drug-like properties, we are going to select the top candidates and test them in chemical and biological assays to validate the drug design approach.”
Targeting CHD1L
Based on research LaBarbera has already conducted, the “lead compounds” with which the quantum computer will be educated are focused on a specific enzyme called CHD1L.
“CHD1L is a chromatin remodeling enzyme that is really critical for what it does in cancer,” he says. “In cancer, it's upregulated, or overexpressed, and it promotes malignant gene expression that leads to tumor progression and metastatic potential. More importantly, we have characterized it as a master regulator of tumor cell survival. When a patient is being treated with chemo or other drug therapies in the clinic, the tumors can often survive because of CHD1L. What we have found with our current lead compounds is that they can synergize with chemotherapy, increasing its potency by a factor of 1,000 in preclinical models.”
In 2022, LaBarbera launched a company called Onconaut Therapeutics to develop CHD1L inhibitors. The company recently received a fast-track small business grant from the National Cancer Institute for $2.5 million.
“Based on our prior research, we selected CHD1L as the proof-of-concept target for this computational study. While our NIH-funded Onconaut program is developing small-molecule CHD1L inhibitors for clinical translation, the AB Nexus project focuses on using quantum-AI technology to explore new chemical space and validate quantum computing as a next-generation drug design approach.”
Better results for patients
Building on promising preclinical data showing that CHD1L inhibition can reduce tumor growth and improve survival in animal models, LaBarbera sees the quantum computing research as a step toward a new era of drug discovery that could accelerate the development of more effective therapies for patients in the future.
“Each year, about two million people are diagnosed with colorectal cancer worldwide, and incidence is rising among adults under 45,” he says. “Roughly half of these patients progress to advanced or metastatic disease, where survival drops to around 13%. Chemotherapy remains the standard of care, yet only about half of patients respond to it, and in some cases, patients decline treatment because of its significant side effects.
“If next-generation colorectal cancer therapies such as CHD1L inhibitors can enhance the effectiveness of frontline chemotherapy and limit drug resistance, we can improve treatment response and patient quality of life,” he continues. “Given the poor survival outcomes for metastatic colorectal cancer, our goal is to develop treatments that extend survival and make the disease more manageable over time.”
Luger, a structural biologist, says using quantum computing will help her and LaBarbera look at the drug development process in three dimensions.
“It will help us come up with lead compounds that we might not have thought of otherwise,” she says. “It seems inconceivable that we are still using the same cancer drugs that we used 40 years ago. We badly need new drug targets and smarter drugs with fewer side effects. Quantum computing applications to cancer drug development is in its infancy, and we have no idea how far it can take us.”
