Because brain cancer cells can be particularly virulent, only the most potent chemotherapies, targeting multiple pathways, may be able to vanquish them. However, such harsh drugs is also destructive to normal tissues. Lemma Pharmaceuticals is addressing this challenge with a targeted delivery technology that encapsulates a highly potent agent and releases it at the site of the tumor, minimizing exposure to the rest of the body.

Lemma was co-founded in 2013 by Santosh Kesari, M.D., Ph.D., Director of Neuro-oncology at the Moores UCSD Cancer Center, members of his research team, and several entrepreneurs. Its launch was made possible by the Kesari team’s discovery, published in October 2013 in International Journal of Nanomedicine, for a novel means to highly and efficiently load microscopic liposomal bubbles with staurosporine (STS) for improved delivery to the site of a brain tumor.

STS is a broad spectrum protein kinase inhibitor with highly potent anticancer effects in test tubes. However, for more than 30 years STS could not be developed as a human therapeutic because it was considered too unstable and too toxic for clinical use. “Staurosporine shows potent activity against a number of cancer cell lines, including chemotherapy-resistant tumors,” Kesari said. “With this study, we have been able to overcome the pharmacokinetic barriers to delivering staurosporine to tumors with the use of liposomes.”

Kesari’s team found a novel method of loading significantly more STS into the liposome microbubbles, almost tripling drug-loading capacity to more than 70 percent. With this delivery system, STS remains in the bloodstream longer without exposing healthy cells to the drug. Thereafter, the microbubbles selectively accumulate at the site of the brain tumor where it delivers the drug in a greater concentration than previously possible. The ability to attack tumor cells with full force is especially significant in chemo-resistant brain cancers.

According to Lemma CEO Thomas Seoh, this innovation is a platform technology, and the company believes it could enable the delivery of diverse anticancer agents that could not previously be safely developed.

“Through improvements in drug delivery technology, patients are gaining access to more potent anticancer agents – payloads that could be too toxic as free-standing drugs have recently been developed as human therapeutics,” said Seoh. “Liposomal encapsulation has been in development for decades as a means of improving the therapeutic index of existing drugs. Based on preliminary animal experiments, our technology may be able to ‘tame and tap’ potent compounds that could otherwise be too toxic and turn them into useful additions to the anticancer armamentarium.”

UC San Diego has filed a patent application on liposomes that can be loaded with STS and similar compounds. Lemma is the exclusive licensee under an innovative Express License structure that facilitates efforts by startup companies to start developing licensed technologies. In experiments using the both formulated drug, and particularly with a tumor targeted version, Kesari’s team has confirmed initial positive animal results in a rigorous animal model which implants human brain cancer cells into the brains of mice.

Liposomal loading of STS has been replicated and further improved at a commercial contract lab that specializes in developing liposomal drugs. “We are now seeking angel seed financing and applying for grants to fund the comparison of STS and several analogs encapsulated in liposomes using this technology actively targeted to tumors,” said Seoh. “We want to select the best agent and formulation in terms of efficacy and tolerability for testing in the clinic as quickly as possible for brain and other cancers.”

Lemma Pharmaceuticals
10225 Barnes Canyon Rd A104 San Diego, CA 92121
Tel: (703) 853-6090
Founded: 2013
Thomas Seoh – President, CEO
Gary Fujii, Ph.D – Chief Scientific Officer


Technology Innovator:


Santosh Kasari, M.D., Ph.D
Professor of Neuroscience,
Director of Neuro-Oncology at Moores Cancer Center