My good friend Logan collins posted this.
Gene therapies can scale economically, but not just with practices adapted from traditional biologics. According to Avantor, gene therapies pose unique material, workflow, and partnering challenges.
Category: biotech/medical – Page 1,615
Using stem cells to create an endless supply of blood
face_with_colon_three circa 2017.
For decades, scientists have sought to create red blood cells in the lab – a “holy grail” that some hoped could ease regional blood shortages, especially for people with rare blood types.
But now British researchers say they have overcome a major barrier that has plagued many scientists: creating enough red cells to fill a blood bag. Their findings are published in the journal Nature Communications.
“When we kept (the cells) continually dividing for a year, we were quite excited,” said Jan Frayne, a biochemist at the University of Bristol and one of the study’s lead authors.
Making melanoma immortal: Pitt scientists discover key genetic step in cancer’s race to live forever
Scientists at the University of Pittsburgh School of Medicine have discovered the missing puzzle piece in the mystery of how melanoma tumors control their mortality.
In a paper published in Science this week, Jonathan Alder, Ph.D. and his team describe how they discovered the perfect combination of genetic alterations that tumors use to promote explosive growth and prevent their own demise, a development that could change the way oncologists understand and treat melanoma.
“We did something that was, in essence, obvious based on previous basic research and connected back to something that is happening in patients,” said Alder, assistant professor in the Division of Pulmonary, Allergy and Critical Care Medicine at Pitt’s School of Medicine.
Amid ‘biotech winter,’ Insilico turns up the heat with Sanofi deal worth $1.2B in biobucks
Insilico Medicine is radiating heat amid the biotech winter, kindling its fires with a Sanofi collaboration that could be worth up to $1.2 billion in biobucks—the AI drug discovery company’s larges | Insilico Medicine is radiating heat amid the biotech winter, kindling its fires with a Sanofi collab that could be worth up to $1.2 billion in biobucks—the AI drug discovery company’s largest deal to date.
First transfusions of lab-grown blood
Recently, two patients in the United Kingdom received two small doses of lab-grown blood samples as part of the RESTORE trial.
Image Credit: Sashkin / Shutterstock.com
About the RESTORE trial
The RESTORE trial is a single-center, randomized, controlled, phase I cross-over trial that is a joint effort between the National Health Service (NHS) Blood and Transplant (NHSBT) and the University of Bristol. The aim of this trial is to determine whether blood cells manufactured from donor stem cells perform better than red blood cells (RBCs) obtained from the same donor in recipients.
Targeting Key Cells in Spinal Cord Got Paralyzed Patients Walking Again
The findings come, in part, from nine patients involved in an ongoing Swiss study that is seeking to restore movement to people with paralysis.
All nine rapidly regained the ability to stand and walk with the help of implants that electrically stimulate spinal nerves that control lower-body movement.
Now the researchers are reporting that they’ve identified a specific group of cells in the lower spine that appear necessary for that movement recovery to happen.
Injections for diabetes, cancer could become unnecessary
Researchers at UC Riverside are paving the way for diabetes and cancer patients to forget needles and injections, and instead take pills to manage their conditions.
Some drugs for these diseases dissolve in water, so transporting them through the intestines, which receive what we drink and eat, is not feasible. As a result, these drugs cannot be administered by mouth. However, UCR scientists have created a chemical “tag” that can be added to these drugs, allowing them to enter blood circulation via the intestines.
The details of how they found the tag, and demonstrations of its effectiveness, are described in a new Journal of the American Chemical Society paper.
How to Catch a Virus
Video surveillance, now viruses.
Duke researchers have captured the first real-time footage of viruses on the move, right before they hijack a cell.
Learn more about the Welsher lab here: https://www.welsherlab.org/
To read the full paper: https://www.nature.com/articles/s41592-022-01672-3
MB01J8TKPYWEHGK.
A Day In The Life Of One Of The Busiest Neuromodulation Clinics On The Planet
This past Monday (Nov. 7th) I was given a behind the scenes look at Dr. Alfonso Fasano’s neuromodulation clinic, one of the busiest of its kind in the world.
On his schedule for that day were about 25 patients, which is fairly typical for him. But these were not exactly 25 patients that a typical doctor might see in a given day. They were patients whom the Canadian medical system had funneled to him, individuals who not even most movement disorder specialists, let alone neurologists or general practitioners, could properly treat. For him and his team though, it was just another Monday.
AI Researchers At Mayo Clinic Introduce A Machine Learning-Based Method For Leveraging Diffusion Models To Construct A Multitask Brain Tumor Inpainting Algorithm
The number of AI and, in particular, machine learning (ML) publications related to medical imaging has increased dramatically in recent years. A current PubMed search using the Mesh keywords “artificial intelligence” and “radiology” yielded 5,369 papers in 2021, more than five times the results found in 2011. ML models are constantly being developed to improve healthcare efficiency and outcomes, from classification to semantic segmentation, object detection, and image generation. Numerous published reports in diagnostic radiology, for example, indicate that ML models have the capability to perform as good as or even better than medical experts in specific tasks, such as anomaly detection and pathology screening.
It is thus undeniable that, when used correctly, AI can assist radiologists and drastically reduce their labor. Despite the growing interest in developing ML models for medical imaging, significant challenges can limit such models’ practical applications or even predispose them to substantial bias. Data scarcity and data imbalance are two of these challenges. On the one hand, medical imaging datasets are frequently much more minor than natural photograph datasets such as ImageNet, and pooling institutional datasets or making them public may be impossible due to patient privacy concerns. On the other hand, even the medical imaging datasets that data scientists have access to could be more balanced.
In other words, the volume of medical imaging data for patients with specific pathologies is significantly lower than for patients with common pathologies or healthy people. Using insufficiently large or imbalanced datasets to train or evaluate a machine learning model may result in systemic biases in model performance. Synthetic image generation is one of the primary strategies to combat data scarcity and data imbalance, in addition to the public release of deidentified medical imaging datasets and the endorsement of strategies such as federated learning, enabling machine learning (ML) model development on multi-institutional datasets without data sharing.