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Category: biotech/medical – Page 1,059

Pfizer, Astellas Pharma‘ Xtandi combo therapy cuts risk of metastasis, death by 58 percent in prostate cancer

“There are patients with localized prostate cancer who undergo prostatectomy or radiation therapy in an attempt to cure their disease, but, unfortunately, some patients will develop BCR,” said Neal Shore, M.D., F.A.C.S., U.S. Chief Medical Officer of Urology and Surgical Oncology, GenesisCare, Director, Carolina Urologic Research Center, and Primary Investigator for the EMBARK study. “Importantly, some patients with BCR are at very high risk for developing metastatic disease, which can lead to a cascade of therapeutic interventions. The clinical goal of BCR therapy is to delay cancer progression and avoid metastatic disease. The MFS results from the EMBARK study demonstrate that this intervention with XTANDI plus leuprolide was statistically significant for patients with high-risk BCR.”

“The EMBARK study is a Phase 3 trial exploring the potential of enzalutamide in patients with non-metastatic hormone-sensitive prostate cancer with high-risk BCR,” said Stephen J. Freedland, M.D., Director of the Center for Integrated Research in Cancer and Lifestyle and the Warschaw Robertson Law Families Chair in Prostate Cancer at Cedars-Sinai Cancer and Co-Principal Investigator of the Clinical Trial. “If approved, we hope to bring a new option to men earlier in the course of their disease.”

Consistent with the study’s primary endpoint, statistically significant and clinically meaningful improvements were also observed in the trial’s key secondary endpoints in both the XTANDI combination and monotherapy arms. Specifically, the XTANDI monotherapy arm demonstrated that treatment with XTANDI reduced the risk of metastasis or death by 37% versus leuprolide plus placebo (HR: 0.63; 95% CI, 0.46–0.87; P=0.0049), meeting its MFS endpoint. Treatment with XTANDI plus leuprolide and XTANDI monotherapy reduced the risk of PSA progression by 93% (HR: 0.07; 95% CI, 0.03–0.14; P0.0001) and 67% (HR: 0.33; 95% CI, 0.23–0.49; P0.0001), respectively, versus placebo plus leuprolide. The progression risk in starting a new antineoplastic therapy was reduced by 64% in those treated with XTANDI plus leuprolide (HR: 0.36; 95% CI, 0.26–0.49; P0.0001) and 46% in those treated with XTANDI monotherapy (HR: 0.54; 95% CI, 0.41–0.71; P0.0001) versus placebo plus leuprolide.

Cannabinoid Agonist Receptor May Have Potential Therapeutic Uses for Rare Autoimmune Disorder

A study in the Journal of Investigative Dermatology suggested that using a cannabinoid receptor type 2 (CB2) agonist called lenabasum may lessen the discomfort caused by amyopathic dermatomyositis. Dermatomyositis is a rare systemic autoimmune disease with distinctive cutaneous features frequently accompanied by muscle inflammation, interstitial lung disease, and malignancy. This phase 2 trial examined the potential benefits of activating the endocannabinoid system to reduce the inflammation causing the symptoms.

Study participants included twenty-two adults diagnosed with moderate to severe skin disease caused by dermatomyositis. They received 20 mg daily of lenabasum or a placebo for 28 days, then 20 mg twice daily for 56 days. Their Cutaneous Dermatomyositis Disease Area and Severity Index (CDASI) levels were evaluated relative to baseline as well as secondary outcomes such as quality of life (measured with the Skindex-29) and specific biomarkers.

More than 40% of the patients taking lenabasum demonstrated significant improvements. The study showed that the CB2 agonist lenabasum improved the skin of amyopathic dermatomyositis patients. The researchers noted that lenabasum was well-tolerated and effective. More than 40% of the patients in the study taking lenabasum demonstrated significant improvements on the CDASI, a validated disease-severity scale. Results showed a trend for the change from baseline CDASI to be greater in lenabasum versus placebo starting at Day 43, two weeks after a dose increase. On Day 113 there was a statistically significant difference between the two groups. The researchers noted that the drug was well tolerated.

Machine learning model finds genetic factors for heart disease

To get an inside look at the heart, cardiologists often use electrocardiograms (ECGs) to trace its electrical activity and magnetic resonance images (MRIs) to map its structure. Because the two types of data reveal different details about the heart, physicians typically study them separately to diagnose heart conditions.

Now, in a paper published in Nature Communications, scientists in the Eric and Wendy Schmidt Center at the Broad Institute of MIT and Harvard have developed a that can learn patterns from ECGs and MRIs simultaneously, and based on those patterns, predict characteristics of a patient’s . Such a tool, with further development, could one day help doctors better detect and diagnose heart conditions from routine tests such as ECGs.

The researchers also showed that they could analyze ECG recordings, which are easy and cheap to acquire, and generate MRI movies of the same heart, which are much more expensive to capture. And their method could even be used to find new genetic markers of heart disease that existing approaches that look at individual data modalities might miss.

AI chatbot outperforms human doctors in responding to patient questions

An artificial intelligence chatbot was able to outperform human doctors in responding to patient questions posted online, according to evaluators in a new study.

Research published in the Journal of the American Medical Association (JAMA) Internal Medicine found that a chatbot’s responses to patient questions, pulled from a social media platform, were rated “significantly higher for both quality and empathy.”

Researchers uncover new clues to origins of the most common pediatric kidney cancer

While Wilms tumor—also known as nephroblastoma—is rare, it is the most prevalent childhood kidney cancer. Researchers at Children’s Hospital Los Angeles have now pinpointed a disruption in early kidney progenitor cell development that can be linked to the formation of Wilms tumor.

In a study published in Advanced Science, researchers at the GOFARR Laboratory in Urology compared kidney progenitor cells from a with from a healthy kidney. Normally, these precursor cells mature into kidney cells, but when their early development is dysregulated, they behave like .

While most children with Wilms tumor are successfully treated, current therapies are aggressive. A minority of these patients have unfavorable prognoses or relapses; for these children, there is no existing therapy. “By achieving a more precise understanding of how Wilms tumors develop, our goal is to find new treatments for all types of Wilms tumor,” says Laura Perin, Ph.D., Co-Director of the GOFARR laboratory and senior study co-author with Stefano Da Sacco, Ph.D., another researcher at the GOFARR Laboratory.

2023 MIT Club of Boston BioSummit

It was an honor to speak at MIT’s Broad Institute about some of my past and present synthetic biology research on redesigning bacteria and viruses to act as delivery systems for biomedicine! Video recording is now available! Here is a link which should take you to 1:40:18 when my talk starts:[ ]. My talk was part of the inaugural MIT Biosummit (https://mitbiosummit.com/), a forward-looking conference which this year focused on tackling challenges at the interface of climate change and health sciences. #futureofmedicine #future #biotech #mit Thank you Ryan Robinson for helping to organize this conference and for giving your own excellent talk!

Recording of the MIT Club of Boston 2023 BioSummit: Human Health 2050 held at the Broad Institute on April 27, 2023. Note: Although the video is almost 6 hours long, you can rapidly navigate and skip to a particular speaker or session by scrubbing along the video timeline (in Chrome or Edge) or using the time markers listed below in blue (in all browsers). You can also use chapter browsing in the YouTube app on platforms where it is available.

Mitbiosummit.com.

0:00:00 Introductory remarks: Ryan Robinson, Whitney Espich.
0:08:44 Morning keynote: Bradley Willcox.
0:57:14 Infectious disease panel introduction, Lindsey Baden.
1:02:21 Kieren Marr.
1:38:27 Speaker transition with Lindsey Baden.
1:39:36 Logan Collins.
1:56:36 Ryan Robinson.
2:13:13 Infectious disease panel Q&A
2:24:00 Longevity panel introduction, Eduardo Cornejo.
2:27:14 Joseph Coughlin.
2:46:47 Vladim Gladyshev.
3:02:28 Cavin Ward-Caviness.
3:18:55 Longevity panel Q&A
3:37:44 Food supply panel introduction, Viji Thomas.
3:48:32 Gary Cohen.
4:05:16 Greg Sixt.
4:21:50 Anirban Kundu.
4:37:32 Food supply panel Q&A
5:15:03 Sebastian Eastham.
5:42:13 Closing remarks, preview of next year’s BioSummit Stephanie Licata.

Scientists develop A.I. system focused on turning peoples’ thoughts into text

Scientists have developed a noninvasive AI system focused on translating a person’s brain activity into a stream of text, according to a peer-reviewed study published Monday in the journal Nature Neuroscience.

The system, called a semantic decoder, could ultimately benefit patients who have lost their ability to physically communicate after suffering from a stroke, paralysis or other degenerative diseases.

“This DNA Is Not Real”: Why Scientists Are Deepfaking the Human Genome

Researchers have taught an AI to make artificial genomes — possibly overcoming the problem of how to protect people’s genetic information while also amassing enough DNA for research.

Generative adversarial networks (GANs) pit two neural networks against each other to produce new, synthetic data that is so good it can pass for real data. Examples have been popping up all over the web — generating pictures and videos (a la “this city does not exist”). AIs can even generate convincing news articles, food blogs, or human faces (take a look here for a complete list of all the oddities created by GANs).

Now, researchers from Estonia are going more in-depth with deepfakes of human DNA. They created an algorithm that repeatedly generates the genetic code of people that don’t exist.