MGH researchers uncover potential antiviral drug target for treating infectious diseases

I want us to disrupt the drug discovery and development process and to look at each place on the drug discovery and development pipeline, so that we can be much better at getting the right target, much quicker at getting the right compound and much more confident that those compounds have the right characteristics which mean they will be safe and well tolerated. Then we can go to the right patient population with the right dose, so we would have a much leaner, more successful process and be able to demonstrate the value of our AI technology.

Daily, if you eat a balanced diet that includes healthy foods, you technically should not need a vitamin supplement. A healthy diet incorporates lean proteins, healthy fats, grains, fruits, and vegetables. But if you do not have a balanced diet, you may be considering hair, skin, and nail vitamins. Some people prefer supplements, sometimes choosing a multivitamin that can supply all of your essential minerals and vitamins. But taking too much of vitamins or unnecessary supplements is wasteful because the body gets rid of excess vitamins and minerals or, worse, it can be dangerous. The following is a guide to choosing which vitamins you may want to consider supplementing and when. Deficiencies in the nutrients that keep the skin, hair, and nails healthy can cause changes over time. For example, not enough intake of vitamins A and E, along with not enough biotin, can cause scaly and rough skin patches, eczema, and hair loss. If there is a deficiency, vitamins will help. However, if there is no deficiency, there is no clear evidence that supplements will make a difference. No research studies concluded that supplements treat or prevent age-related, natural hair damage or loss or lead to healthier skin. Two studies in the early 1990s did suggest that a biotin supplement may cause the hair to become stronger and strengthen weak nails. However, the studies were small and not reproduced.

RAS mutations are one of the most common cancer-causing genetic mutations, and the drug is now being studied in several cancer types. I think it's going to work especially well in tumors that are primarily RAS driven, including colon cancer and lung cancer. It might also work in other cancer types in combination with drugs targeting other genetic mutations, but further research is needed.

Carb cycling is an attempt to fine-tune your carbohydrate consumption to alter many aspects of your metabolism. Your plan will include the same protein intake each day but vary carbohydrates according to your activity. Your carb cycling plan may have three low or zero carb days, two moderate carb days, and two high carb days. Meeting your calorie requirements will require including more fats on low-carb days. Carb cycling needs much more planning than a usual calorie-controlled diet. One way is to match your carb cycling to your physical activity. If you go to the gym thrice a week, you could have carbs on those days. The carbs provide energy for your workout, prevent fatigue, and avoid the muscle loss sometimes seen with dieting. The days when you eat little to no carbs force your body to generate energy from other sources, like proteins and fats. But the days when you eat more carbohydrates might reverse this change. You must only eat a high-carb diet on the days you have a heavy workout, which uses up the calories.

Uncertainty and model limitations are critical in safety assessment. There is clearly greater potential for animal or human harm from an incorrect safety assessment than from making the wrong molecule in early discovery, although uncertainty matters in both contexts. It is important to distinguish different types of uncertainty. Aleatoric uncertainty reflects irreducible randomness in a task, while epistemic uncertainty is model-related, such as hallucinations or lack of knowledge. For LLM systems, we use multiple methods to measure consistency and we have built fact-checking approaches in which a separate LLM independently verifies the primary engine's outputs. For QSAR models, including our SAR work around seizure liability, we can use statistical metrics such as confidence intervals to quantify and communicate uncertainty. Understanding that uncertainty exists and communicating it in both safety and discovery is critical. Uncertainty metrics tell us where potential blind spots may exist in our modelling allowing us to take action to improve over time. This applies to both safety and discovery. The aim is not to pretend AI removes uncertainty, but to make uncertainty visible so scientists can make better-informed decisions. Download the Full PDF to Revisit James McDonagh's Insights on AI in Drug Safety Discovery