Dr. Desikan studies the effectiveness of antiviral drugs, especially in relation to COVID-19, using mathematical formulas to better understand how these medications work. He investigates conditions such as multiple myeloma, where he examines treatments like stem cell transplants and compares different types of transplants to find the most effective options for patients. Through his work, he aims to help doctors and patients navigate complex treatment decisions and enhance the efficacy of drugs in various medical scenarios.
Key findings
In his 2023 study on antiviral drugs, Dr. Desikan found that new mathematical formulas could help predict the effectiveness of medications like Remdesivir and Chloroquine for COVID-19 treatment.
In a 2023 publication, he demonstrated that newly developed topological indices provided better predictions of benzenoid hydrocarbons' properties than existing methods.
From a study of 88 myeloma patients, it was found that 76% could collect enough stem cells for future use despite delays or incomplete recovery of platelets.
In a comparison of treatment outcomes, 54% of patients who received an autologous transplant were alive after three years, compared to only 29% of those who underwent an allogeneic transplant. However, 31% of allogeneic patients had their disease worsen compared to 72% of autologous patients after three years.
Frequently asked questions
Does Dr. Desikan study COVID-19 treatments?
Yes, Dr. Desikan examines antiviral drugs used for COVID-19 and works on improving how we evaluate their effectiveness.
What types of cancer does Dr. Desikan focus on?
Dr. Desikan primarily focuses on multiple myeloma, a type of blood cancer, and researches new treatment options like stem cell transplants.
What is the significance of Dr. Desikan's work on stem cell transplants?
His research highlights the challenges patients face with platelet recovery after stem cell collection and compares the outcomes of different transplant methods.
What methods does Dr. Desikan use in his research?
He utilizes mathematical modeling and analysis techniques to predict the properties and effectiveness of various medical treatments.
Publications in plain English
Curvilinear regression analysis of benzenoid hydrocarbons and computation of some reduced reverse degree based topological indices for hyaluronic acid-paclitaxel conjugates.
2023
Scientific reports
Ravi V, Desikan K
Plain English This study examined new methods for predicting the properties of certain chemical compounds known as benzenoid hydrocarbons and how well these predictions can indicate their behavior in the body. Researchers found that using newly developed mathematical indices made better predictions of these compounds' characteristics than existing methods. Specifically, they showed that these new indices can effectively predict properties of benzenoid hydrocarbons, helping to refine how we understand and use these compounds in medicine.
Who this helps: This research benefits doctors and scientists working with drug development.
QSPR/QSAR analysis of some eccentricity based topological descriptors of antiviral drugs used in COVID-19 treatment via $ \mathscr{D}\varepsilon $- polynomials.
2023
Mathematical biosciences and engineering : MBE
Sarkarai D, Desikan K
Plain English This study examined how certain mathematical formulas can help understand the properties of antiviral drugs used to treat COVID-19. Researchers analyzed eight medications, including Remdesivir and Chloroquine, and developed new ways to evaluate their effectiveness and properties. They found that using these new formulas could help predict how well these drugs work, which is important for creating better treatments for COVID-19.
Who this helps: This benefits patients and doctors looking for effective COVID-19 treatments.
Plain English This study looked at 88 myeloma patients who had previously undergone stem cell transplants but did not have stored stem cells for future treatments. The researchers found that while most patients (76%) could collect enough stem cells for future use, recovery of platelets after using these cells was often delayed or incomplete in many cases. This is important because it highlights that while collecting stem cells can be done, patients may face challenges with platelet recovery that could impact their treatment options.
Who this helps: This helps patients with myeloma and other blood cancers who may need future stem cell treatments.
Salvage autologous or allogeneic transplantation for multiple myeloma refractory to or relapsing after a first-line autograft?
1998
Bone marrow transplantation
Mehta J, Tricot G, Jagannath S, Ayers D, Singhal S +8 more
Plain English This study looked at 42 patients with multiple myeloma who received a second transplant after their first one failed. The researchers compared these patients, who had an allogeneic transplant (from a donor), with 42 similar patients who had an autologous transplant (using their own cells). They found that 54% of patients who had an autologous transplant were alive three years later, compared to only 29% of those who had an allogeneic transplant. However, patients who received allogeneic transplants had a lower rate of their disease worsening after three years (31% compared to 72%).
Who this helps: This research benefits patients with multiple myeloma who are exploring their options for treatment after their first transplant.