The hope to improve people’s lives is what drives many members of industry and academia to bring new products and therapies to market. At the BIO International Convention last week in Boston, there was lots of discussion about how translational science intersects with patients’ needs and why the best therapeutic developmental pipelines are consistently putting patients first.
“Our mission is to de-risk entry of new therapies in the ASD drug discovery and development space,” said Sahin, who is also a professor of neurology at Harvard Medical School.
One big challenge, says Sahin, is knowing how well — or how poorly — autism therapies are actually affecting people with ASD. Externally, ASD is recognized by its core symptoms of repetitive behaviors and social deficits. …
This is part I of a two-part blog series recapping the 2018 BIO International Convention.
At the 2018 BIO International Convention last week, it was clear what’s provoking scientific minds in industry and academia — or at least those of the Guinness-world-record-making 16,000 people in attendance. Artificial intelligence, machine learning and their implications for tailor-made medicine bubbled up across all BIO’s educational tracks and a majority of discussions about the future state of biotechnology. Panelists from Boston Children’s Hospital also contributed their insights to what’s brewing at the intersection of these burgeoning fields.
Isaac Kohane, MD, PhD, former chair of Boston Children’s Computational Health and Informatics Program, spoke on a panel about how large-scale patient data — if properly harnessed and analyzed for health and disease trends — is a virtual goldmine for precision medicine insights. Patterns gleaned from population health data or electronic health records, for example, could help identify which subgroups of patients who might respond better to specific therapies.
According to Kohane, who is currently the Marion J. Nelson Professor of Biomedical Informatics and Pediatrics at Harvard Medical School (HMS), we will soon be leveraging artificial intelligence to go through patient records and determine exactly what doctors were thinking when they saw patients.
“We’ve seen again and again that data abstraction by artificial intelligence is better than abstraction by human analysts when performed at the scale of millions of clinical notes across thousands of patients,” said Kohane.
And based on what we heard at BIO, artificial intelligence will revolutionize more than patient data mining. It will also transform the way we design precision therapeutics — and even vaccines — from the ground up. …
David Ludwig, MD, PhD, an endocrinologist at Boston Children’s Hospital, has written popular books espousing a low-glycemic, low-carbohydrate diet for weight control. He has argued that high-glycemic diets are contributing to the epidemic of type 2 diabetes. But he hadn’t given much thought to carbohydrate restriction for type 1 diabetes until 2016.
At a conference, Ludwig met a surgeon with type 1 diabetes who maintains normal hemoglobin A1c levels (indicating high blood sugar control) on a very-low-carbohydrate diet. This surprised and impressed him: he had never seen any patient with type 1 diabetes able to completely normalize their hemoglobin A1cs. Moreover, most diabetes experts discourage very-low-carb diets, believing they pose a risk for hypoglycemia, or a dangerous drop in blood sugar. …
Ribonucleic acid, or RNA, has long been underappreciated for its role in gene expression. Until recent years, RNA has been thought of merely as a messenger, shuttling DNA’s instructions to the genetic machinery that synthesizes proteins.
But new discoveries of RNA functions, modifications and its ability to transcribe sections of the genome that were previously considered “junk DNA” has led to the discovery of a huge number of new druggable targets.
These new insights into RNA’s complex purposes have largely been uncovered through ever-increasingly sensitive and affordable sequencing methods. As a result, RNA-based drugs now stand to greatly extend our ability to treat diseases beyond the scope of what’s possible with small molecules and biologics.
Lieberman, who has helped pioneer the RNA-based drug revolution herself, was the first scientist to show in an animal disease model that small, double-stranded RNAs could be used as drugs and leveraged to knock down genes in cells.
What drives me as a scientist has changed over the course of my career. It was my fascination with experimentation that first got me interested in biology. In high school, I took vials of fruit flies to a radiation oncology department and tested the effects of radiation on the mutation rate. When I came to the U.S. to study biochemistry in college, I was drawn to the mysteries of the brain. While my PhD and postdoctoral work continued on very fundamental questions about how neurons connect to each other, advances in genetics and neuroscience allowed me to bring rigorous basic science approaches to clinical questions. So more and more, my science is driven by a need to bring treatments to the patients I see in the clinic. Fortunately, this is no longer a long-term, aspirational goal, but something within reach in my career. …
Like all cells, the neurons of our nervous system depend on mitochondria to generate energy. Mitochondria need constant rejuvenation and turnover, and that’s especially true in neurons because of their high energy needs for signaling and “firing.” Mitochondria are especially abundant at presynaptic sites — the tips of axons that form synapses or junctions with other neurons and release neurotransmitters.
But the process of maintaining mitochondrial number and quality, known as mitostasis, also poses particular challenges in neurons. Increasingly, mitostasis is providing a helpful lens for understanding neurodegenerative disorders. Problems with mitostasis are implicated in Parkinson’s disease, Alzheimer’s disease, ALS, autism, stroke, multiple sclerosis, hypoxia and more. …
How can the growing number of digital health startups sell their products to large-scale healthcare enterprises? Earlier this year, Rock Health, a San Francisco-based venture fund dedicated to digital health, conducted 30-minute interviews with executives at multiple startups and a few large healthcare organizations. They identified several key sticking points: navigating the internal complexities of hospitals, finding the right buyer, identifying the product’s value proposition and relevance to the hospital and avoiding “death by pilot.”