Recent Advances in Drug Development

One in eight women is being diagnosed with breast cancer in her lifetime .Chemotherapy, which is one of the most followed therapy for cancer results in destroying the First –line cancer DNA-creating proteins, but BRCA genes have a backup plan that repairs the DNA and is carried out by poly-ADP-ribose polymerases (PARPs).

The new class of breast cancer drug Abemaciclib, which belongs to CDK4/6 inhibitors have shown the most positive effect on metastatic breast cancer, especially in HER2+ breast cancers .This was designed as the breakthrough therapy Abemaciclib and is armed with certain advantages over its rivals. The clinical studies results have put Abemaciclib roughly on par with its competitors in the first-line setting. Side effects that occurred in 20% or more of patients in studies were diarrhoea, nausea and vomiting, leukopenia. Verzenio is another type of medicine which is used to treat a type of breast cancer called HR+/HER2− (hormone receptor positive/human epidermal growth factor receptor 2 negative) and the cancer has spread to other parts of the body .This drug is given in combination with an aromatase inhibitor as initial endocrine-based therapy for the treatment of postmenopausal women or alone in women whose disease has progressed after hormone therapy and prior chemotherapy. Another new class of drug has been developed for the LDL –Cholesterol .The mechanism involves the lowering of cholesterol at higher levels which is proved to be ground breaking. The experiment which is performed with statin cholesterol drug, the new class of drugs is expected to lower cholesterol levels by 75%.The small interfering RNA therapy to lower LDL was given twice a year instead of monthly or weekly like other treatments. They are set to develop new class of agents to lower the LDL levels which will be launched in 2018.

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How Machine Learning Can Power Drug Discovery

A recent assessment of the success of the drug development process put the percentage of phase I programs that make it to approval at just 13.8%. That’s not great, and while It’s not as bad as some earlier estimates, nonetheless points to a crisis of attrition within the industry. Netramark, a Toronto-based start-up, claim they have a solution to that crisis. Leveraging various machine-learning based methods from machine learning, Netramark aim to give new life to failing and failed drugs by revealing specific sub-populations that treatments may prove successful in, whilst reducing clinical trial size to enable savings for industry. It’s an exciting idea, and we recently spoke to Netramark founder Dr. Joseph Geraci to discover more about the company’s technology, and how machine learning and quantum computing may make drug development easier for clinicians, scientists, and patients.

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