#drug development

[unbfacts]

[mysticalmindshop1]

I’m loaded on ecstasy

[cbirt]

A team of researchers from the University of Chinese Academy of Sciences, China, and collaborators developed GeneCompass, one of the first foundation models of its kind that encompasses a vast expanse of knowledge across a diverse array of species, owing to the fact that it has been trained on over 120 million single-cell transcriptomes derived from the genomes of mice and humans. It is a self-supervised model. During the process of pre-training the model, it retrieves information from four types of biological datasets in the form of ‘prior knowledge’ and integrates it. It has excelled and outperformed several state-of-the-art models when studying a single species. It can also open new avenues for carrying out studies across different combinations of species other than humans and mice. This model can potentially contribute to discovering key regulators that determine cell fate and to identifying promising target candidates in the drug discovery and development field.

It is essential to decode universal regulatory mechanisms that dictate the expression of genes across a diverse set of organisms for accelerating clinical research and expanding our existing knowledge of basic and crucial life processes. Traditional research methodologies and existing deep-learning models have only considered using individual models of organisms separately. This has resulted in a dearth of integrated knowledge of features observed across different cell types over a variety of species. The development of this model was made possible by combining the outcomes of recent advancements in the fields of deep-learning (DL) methods and single-cell sequencing methods.

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[jcmarchi]

Cellular traffic congestion in chronic diseases suggests new therapeutic targets

New Post has been published on https://thedigitalinsider.com/cellular-traffic-congestion-in-chronic-diseases-suggests-new-therapeutic-targets/

Cellular traffic congestion in chronic diseases suggests new therapeutic targets

Chronic diseases like Type 2 diabetes and inflammatory disorders have a huge impact on humanity. They are a leading cause of disease burden and deaths around the globe, are physically and economically taxing, and the number of people with such diseases is growing.

Treating chronic disease has proven difficult because there is not one simple cause, like a single gene mutation, that a treatment could target. At least, that’s how it has appeared to scientists. However, new research from MIT professor of biology and Whitehead Institute for Biomedical Research member Richard Young and colleagues, published in the journal Cell on Nov. 27, reveals that many chronic diseases have a common denominator that could be driving their dysfunction: reduced protein mobility. 

What this means is that around half of all proteins active in cells slow their movement when cells are in a chronic disease state, reducing the proteins’ functions. The researchers’ findings suggest that protein mobility may be a linchpin for decreased cellular function in chronic disease, making it a promising therapeutic target.

In their paper, Young and colleagues in his lab, including MIT postdoc Alessandra Dall’Agnese, graduate students Shannon Moreno and Ming Zheng, and Research Scientist Tong Ihn Lee, describe their discovery of this common mobility defect, which they call proteolethargy; explain what causes the defect and how it leads to dysfunction in cells; and propose a new therapeutic hypothesis for treating chronic diseases.

“I’m excited about what this work could mean for patients,” says Dall’Agnese. “My hope is that this will lead to a new class of drugs that restore protein mobility, which could help people with many different diseases that all have this mechanism as a common denominator.”

“This work was a collaborative, interdisciplinary effort that brought together biologists, physicists, chemists, computer scientists and physician-scientists,” Lee says. “Combining that expertise is a strength of the Young lab. Studying the problem from different viewpoints really helped us think about how this mechanism might work and how it could change our understanding of the pathology of chronic disease.”

Commuter delays cause work stoppages in the cell

How do proteins moving more slowly through a cell lead to widespread and significant cellular dysfunction? Dall’Agnese explains that every cell is like a tiny city, with proteins as the workers who keep everything running. Proteins have to commute in dense traffic in the cell, traveling from where they are created to where they work. The faster their commute, the more work they get done. Now, imagine a city that starts experiencing traffic jams along all the roads. Stores don’t open on time, groceries are stuck in transit, meetings are postponed. Essentially all operations in the city are slowed.

The slowdown of operations in cells experiencing reduced protein mobility follows a similar progression. Normally, most proteins zip around the cell bumping into other molecules until they locate the molecule they work with or act on. The slower a protein moves, the fewer other molecules it will reach, and so the less likely it will be able to do its job. Young and colleagues found that such protein slowdowns lead to measurable reductions in the functional output of the proteins. When many proteins fail to get their jobs done in time, cells begin to experience a variety of problems — as they are known to do in chronic diseases.

Discovering the protein mobility problem

Young and colleagues first suspected that cells affected in chronic disease might have a protein mobility problem after observing changes in the behavior of the insulin receptor, a signaling protein that reacts to the presence of insulin and causes cells to take in sugar from blood. In people with diabetes, cells become less responsive to insulin — a state called insulin resistance — causing too much sugar to remain in the blood. In research published on insulin receptors in Nature Communications in 2022, Young and colleagues reported that insulin receptor mobility might be relevant to diabetes.

Knowing that many cellular functions are altered in diabetes, the researchers considered the possibility that altered protein mobility might somehow affect many proteins in cells. To test this hypothesis, they studied proteins involved in a broad range of cellular functions, including MED1, a protein involved in gene expression; HP1α, a protein involved in gene silencing; FIB1, a protein involved in production of ribosomes; and SRSF2, a protein involved in splicing of messenger RNA. They used single-molecule tracking and other methods to measure how each of those proteins moves in healthy cells and in cells in disease states. All but one of the proteins showed reduced mobility (about 20-35 percent) in the disease cells. 

“I’m excited that we were able to transfer physics-based insight and methodology, which are commonly used to understand the single-molecule processes like gene transcription in normal cells, to a disease context and show that they can be used to uncover unexpected mechanisms of disease,” Zheng says. “This work shows how the random walk of proteins in cells is linked to disease pathology.”

Moreno concurs: “In school, we’re taught to consider changes in protein structure or DNA sequences when looking for causes of disease, but we’ve demonstrated that those are not the only contributing factors. If you only consider a static picture of a protein or a cell, you miss out on discovering these changes that only appear when molecules are in motion.”

Can’t commute across the cell, I’m all tied up right now

Next, the researchers needed to determine what was causing the proteins to slow down. They suspected that the defect had to do with an increase in cells of the level of reactive oxygen species (ROS), molecules that are highly prone to interfering with other molecules and their chemical reactions. Many types of chronic-disease-associated triggers, such as higher sugar or fat levels, certain toxins, and inflammatory signals, lead to an increase in ROS, also known as an increase in oxidative stress. The researchers measured the mobility of the proteins again, in cells that had high levels of ROS and were not otherwise in a disease state, and saw comparable mobility defects, suggesting that oxidative stress was to blame for the protein mobility defect.

The final part of the puzzle was why some, but not all, proteins slow down in the presence of ROS. SRSF2 was the only one of the proteins that was unaffected in the experiments, and it had one clear difference from the others: its surface did not contain any cysteines, an amino acid building block of many proteins. Cysteines are especially susceptible to interference from ROS because it will cause them to bond to other cysteines. When this bonding occurs between two protein molecules, it slows them down because the two proteins cannot move through the cell as quickly as either protein alone. 

About half of the proteins in our cells contain surface cysteines, so this single protein mobility defect can impact many different cellular pathways. This makes sense when one considers the diversity of dysfunctions that appear in cells of people with chronic diseases: dysfunctions in cell signaling, metabolic processes, gene expression and gene silencing, and more. All of these processes rely on the efficient functioning of proteins — including the diverse proteins studied by the researchers. Young and colleagues performed several experiments to confirm that decreased protein mobility does in fact decrease a protein’s function. For example, they found that when an insulin receptor experiences decreased mobility, it acts less efficiently on IRS1, a molecule to which it usually adds a phosphate group.

From understanding a mechanism to treating a disease

Discovering that decreased protein mobility in the presence of oxidative stress could be driving many of the symptoms of chronic disease provides opportunities to develop therapies to rescue protein mobility. In the course of their experiments, the researchers treated cells with an antioxidant drug — something that reduces ROS — called N-acetyl cysteine and saw that this partially restored protein mobility. 

The researchers are pursuing a variety of follow-ups to this work, including the search for drugs that safely and efficiently reduce ROS and restore protein mobility. They developed an assay that can be used to screen drugs to see if they restore protein mobility by comparing each drug’s effect on a simple biomarker with surface cysteines to one without. They are also looking into other diseases that may involve protein mobility, and are exploring the role of reduced protein mobility in aging.

“The complex biology of chronic diseases has made it challenging to come up with effective therapeutic hypotheses,” says Young. “The discovery that diverse disease-associated stimuli all induce a common feature, proteolethargy, and that this feature could contribute to much of the dysregulation that we see in chronic disease, is something that I hope will be a real game-changer for developing drugs that work across the spectrum of chronic diseases.”

[scientificinquirer-blog]

DAILY DOSE: Hurricane Beryl Nears Grenada as Category 4 Threat; Moderna Seeks FDA Nod for Dual COVID-Flu Shot.

HURRICANE BERYL INTENSIFIES, MENACES ISLANDS WITH CATASTROPHIC IMPACT Hurricane Beryl escalated to a Category 4 storm as it moved through the Windward Islands, threatening communities with severe storm surge, destructive winds, and flash flooding. Particularly at risk were St. Vincent, the Grenadines, and Grenada, with Beryl positioned 70 miles east of Grenada, featuring 130 mph winds. While a…

[sanguinifex]

This is huge. As of 8/30/2023, the Federal Department of Health and Human Services wants the DEA to reclassify from schedule 1 (no medical use, completely verboten) to schedule 3 (widely accepted medical use, some abuse potential, similar to Tylenol 3).

It won’t just allow doctors to prescribe it and reduce the penalties for having it if you’re not “supposed to”; it’ll also make it much easier for researchers to do studies with it, giving us health data that is currently lacking. For example, we don’t know much about how THC and CBD affect the liver or liver enzyme levels except in end stage liver disease patients, and what data we do have is decades old and of poor to middling quality.

The expansion of research a Schedule 3 reclassification would allow could pave the way for a safe, non-addictive pain medication based on cannabinoids that works primarily on the CB2 receptors and either doesn’t pass the blood-brain barrier or does cross it but doesn’t cause euphoria or sedation in most patients. In other words, the holy grail of pain medicine. Currently, the only painkiller that utilizes the endocannabinoid system is acetaminophen (Tylenol), which is a weak reuptake inhibitor of anandamide but primarily works via the prostaglandin system, and which is also highly hepatotoxic and somewhat nephrotoxic, and which probably wouldn’t be approved except as prescription fever and pain management, the latter primarily as an adjuvant to opiates, if it were a new drug being reviewed by the FDA today.

This is a really big example of how both parties are not the same. A Republican administration DHHS wouldn’t do this. If the No Fun Allowed Agency follows instructions, this opens up a lot of possibilities for a lot of people. It also completely bypasses the partisan legislatures and courts. Technically it’s easier for a future administration to overturn, but historically the DEA rarely reschedules medications without strong external pressure. (And in this case, it’s already functionally legal for those 21+ in most of the country anyway.)

[intrinsequehealth]

Intrinseque Health - Clinical Supply Chain We Build and Execute Complex Clinical Supply Plans

Intrinseque Health is an EN ISO 13485 Certified Global clinical trial support services provider committed to the utmost in service delivery to drug development organizations (Pharmaceutical, Biotechnology, Medical Device & Contract Research Organizations (CROs)). Our team of industry professionals has over 300 years of combined experience supporting global clinical trials across a wide array of therapeutic areas. This vast experience enables us to empathize with our Customers while providing best-in-class solutions to overcome the hurdles and pain-points of conducting a clinical trial.

Regions & countries throughout the world will often present a unique set of regulatory and logistical challenges. It is our responsibility to understand and overcome these while ensuring that your products, supplies, equipment and services are available where needed to ensure study timelines are met. Intrinseque Health utilizes an operational methodology that is based on proven, cost-effective clinical supply chain strategy for each clinical trial. Our practice is to engage with our customers, early and often to ensure implementation of a robust clinical supply plan, resulting in the most successful study start-up and initiation.

[sbgridconsortium]

Ligand and G-protein selectivity in the κ-opioid receptor

The dark history of opioids use in pain management is a testament to the complexity that comes with discovering potential drug targets in the brain. The therapeutic target of opioids is usually the μ-opioid receptor (MOR). This interaction between the MOR and opioids creates the sensation of pain relief by the downstream signaling of the MOR through the Gi/o-family proteins. Sadly, MOR has downstream effects that can cause outcomes other than diminishing pain, like addiction and abuse. 

For this reason, other viable targets for pain management are important in trying to lessen dependence on opioids. One way to lessen the unintended consequences of opioids while still effectively managing pain is to target pathways relevant to pain relief downstream of the MOR while avoiding pathways that cause other effects. One possible target could be the κ-opioid receptor (KOR). This receptor targets similar downstream effects responsible for the pain reducing effects of the MOR, while not causing the similar levels of addiction. The KOR does however, tend to cause hallucinogenic symptoms when targeted. 

Above: Published structure of KOR bound to Gg protein. PDB: 8DZR. CC BY SBGRID

To provide insight on this effect, SBGrid member Tao Che and collaborators studied how ligand binding to KOR affects its signaling machinery, the Gi/o-family proteins. Using cryo-EM, they studied the specificity of the KOR to ligands and the selectivity of four types of Gi/o-family proteins to the KOR/ligand complexes. From these structures the authors are able to determine a high level of selectivity of KOR to specific ligands and high levels of selectivity of G proteins to KOR/ligand complexes. The specificity of certain Gi/o-family proteins to certain KOR/ligand complexes could suggest that therapeutics can be designed to not only target the KOR, but also select desired downstream pathways by signaling through specific Gi/o-family proteins.

Read more about this work in Nature.

-Vida Storm Robertson, Fisk University

[white-throated-packrat]

As someone who works in pharma development, after the animal trials are over and the results are that it DOES work as intended and it doesn’t seem to be toxic (but non-human animals can process drugs differently from humans, so it’s not a guarantee), you move to Phase I drug testing.

Phase I testing IS giving microdoses of your Investigational New Drug to healthy human volunteers, and checking them for reactions. The entire trial is approved by the FDA before you start, you monitor everything very carefully, compile your data, and only when the FDA has reviewed it and agrees that it is safe to proceed do you move to Phase II testing.

Phase II testing is when you give the new drug to patients in the intended target patient population at the actual therapeutic dose. Recruiting volunteers is difficult, because most people don’t want to take experimental drugs, especially when they do have a treatment plan that works for them. The Phase II teasting is also approved by the FDA before it starts.

Phase III testing is on a larger group of patients, since Phase II is on a small group, which might skew the results because small groups are not necessary representational samples of the entire patient population. This is also approved by the FDA.

It takes years to develop a new drug, because you have to do so much testing. Because the alternative is the Elixir Sulfanilimide Disaster, or Thalidomide .

the cognitive dissonance from people who want the products of modern medicine but get weird about animal research. like im sorry but this is necessary for the survival of the society we currently live in. and the scientists who work on these things are not evil cackling psychopaths. anyone you talk to in animal research has incredibly complex feelings about their work and incredibly complex relationships to the animals in their care. there are regulations and oversight and penalties in place to make the work as humane as possible and scientists are overwhelmingly the ones enforcing and advocating for better care.

[biopharmaceuticalindustry]

Blockchain: Mandatory in Constructing a High-fidelity Database Readying for The Downstream Disruptive Technologies, such as for The Artificial Intelligence Training

Author: Frank Leu, Founder and managing member, BioPharMatrix LLC

Blockchain is the foundation layer for the data procured during drug development that is transparent, secure, and traceable. This tamper-proof and decentralised ledger also ensures that data generated during drug development is both robust and accessible to all stakeholders while allowing machine learning and artificial intelligence to harness data effectively and provide accurate solutions.

Learn more: https://www.pharmafocusasia.com/information-technology/blockchain-mandatory-constructing-high-fidelity-batabase

[cbirt]

A team of researchers at the University of California, San Diego, came together to develop a chatbot specifically catered to drug discovery called DrugChat. It is similar to ChatGPT on the basis that users can give question prompts to the model on any drug compound under study after uploading the drug’s molecular graph and can get answers to their queries in an interactive and iterative manner. It is composed of a graph neural network (GNN), a large language model (LLM), and an adaptor.

Traditional methods of drug discovery, which have been carried out experimentally, have been expensive and time-consuming. Approval for even a single drug to go up in pharmaceutical stores for sale takes several years and a lot of money. Experimental methods also require a lot of labor and step-by-step testing, often ending up in failure at the last few stages of drug development. Taking advantage of artificial intelligence (AI) to mitigate these issues is crucial in today’s fast-paced and demanding world, where novel drugs are needed to treat an ever-increasing list of diseases.

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[jcmarchi]

Unlocking mRNA’s cancer-fighting potential

New Post has been published on https://thedigitalinsider.com/unlocking-mrnas-cancer-fighting-potential/

Unlocking mRNA’s cancer-fighting potential

What if training your immune system to attack cancer cells was as easy as training it to fight Covid-19? Many people believe the technology behind some Covid-19 vaccines, messenger RNA, holds great promise for stimulating immune responses to cancer.

But using messenger RNA, or mRNA, to get the immune system to mount a prolonged and aggressive attack on cancer cells — while leaving healthy cells alone — has been a major challenge.

The MIT spinout Strand Therapeutics is attempting to solve that problem with an advanced class of mRNA molecules that are designed to sense what type of cells they encounter in the body and to express therapeutic proteins only once they have entered diseased cells.

“It’s about finding ways to deal with the signal-to-noise ratio, the signal being expression in the target tissue and the noise being expression in the nontarget tissue,” Strand CEO Jacob Becraft PhD ’19 explains. “Our technology amplifies the signal to express more proteins for longer while at the same time effectively eliminating the mRNA’s off-target expression.”

Strand is set to begin its first clinical trial in April, which is testing a proprietary, self-replicating mRNA molecule’s ability to express immune signals directly from a tumor, eliciting the immune system to attack and kill the tumor cells directly. It’s also being tested as a possible improvement for existing treatments to a number of solid tumors.

As they work to commercialize its early innovations, Strand’s team is continuing to add capabilities to what it calls its “programmable medicines,” improving mRNA molecules’ ability to sense their environment and generate potent, targeted responses where they’re needed most.

“Self-replicating mRNA was the first thing that we pioneered when we were at MIT and in the first couple years at Strand,” Becraft says. “Now we’ve also moved into approaches like circular mRNAs, which allow each molecule of mRNA to express more of a protein for longer, potentially for weeks at a time. And the bigger our cell-type specific datasets become, the better we are at differentiating cell types, which makes these molecules so targeted we can have a higher level of safety at higher doses and create stronger treatments.”

Making mRNA smarter

Becraft got his first taste of MIT as an undergraduate at the University of Illinois when he secured a summer internship in the lab of MIT Institute Professor Bob Langer.

“That’s where I learned how lab research could be translated into spinout companies,” Becraft recalls.

The experience left enough of an impression on Becraft that he returned to MIT the next fall to earn his PhD, where he worked in the Synthetic Biology Center under professor of bioengineering and electrical engineering and computer science Ron Weiss. During that time, he collaborated with postdoc Tasuku Kitada to create genetic “switches” that could control protein expression in cells.

Becraft and Kitada realized their research could be the foundation of a company around 2017 and started spending time in the Martin Trust Center for MIT Entrepreneurship. They also received support from MIT Sandbox and eventually worked with the Technology Licensing Office to establish Strand’s early intellectual property.

“We started by asking, where is the highest unmet need that also allows us to prove out the thesis of this technology? And where will this approach have therapeutic relevance that is a quantum leap forward from what anyone else is doing?” Becraft says. “The first place we looked was oncology.”

People have been working on cancer immunotherapy, which turns a patient’s immune system against cancer cells, for decades. Scientists in the field have developed drugs that produce some remarkable results in patients with aggressive, late-stage cancers. But most next-generation cancer immunotherapies are based on recombinant (lab-made) proteins that are difficult to deliver to specific targets in the body and don’t remain active for long enough to consistently create a durable response.

More recently, companies like Moderna, whose founders also include MIT alumni, have pioneered the use of mRNAs to create proteins in cells. But to date, those mRNA molecules have not been able to change behavior based on the type of cells they enter, and don’t last for very long in the body.

“If you’re trying to engage the immune system with a tumor cell, the mRNA needs to be expressing from the tumor cell itself, and it needs to be expressing over a long period of time,” Becraft says. “Those challenges are hard to overcome with the first generation of mRNA technologies.”

Strand has developed what it calls the world’s first mRNA programming language that allows the company to specify the tissues its mRNAs express proteins in.

“We built a database that says, ‘Here are all of the different cells that the mRNA could be delivered to, and here are all of their microRNA signatures,’ and then we use computational tools and machine learning to differentiate the cells,” Becraft explains. “For instance, I need to make sure that the messenger RNA turns off when it’s in the liver cell, and I need to make sure that it turns on when it’s in a tumor cell or a T-cell.”

Strand also uses techniques like mRNA self-replication to create more durable protein expression and immune responses.

“The first versions of mRNA therapeutics, like the Covid-19 vaccines, just recapitulate how our body’s natural mRNAs work,” Becraft explains. “Natural mRNAs last for a few days, maybe less, and they express a single protein. They have no context-dependent actions. That means wherever the mRNA is delivered, it’s only going to express a molecule for a short period of time. That’s perfect for a vaccine, but it’s much more limiting when you want to create a protein that’s actually engaging in a biological process, like activating an immune response against a tumor that could take many days or weeks.”

Technology with broad potential

Strand’s first clinical trial is targeting solid tumors like melanoma and triple-negative breast cancer. The company is also actively developing mRNA therapies that could be used to treat blood cancers.

“We’ll be expanding into new areas as we continue to de-risk the translation of the science and create new technologies,” Becraft says.

Strand plans to partner with large pharmaceutical companies as well as investors to continue developing drugs. Further down the line, the founders believe future versions of its mRNA therapies could be used to treat a broad range of diseases.

“Our thesis is: amplified expression in specific, programmed target cells for long periods of time,” Becraft says. “That approach can be utilized for [immunotherapies like] CAR T-cell therapy, both in oncology and autoimmune conditions. There are also many diseases that require cell-type specific delivery and expression of proteins in treatment, everything from kidney disease to types of liver disease. We can envision our technology being used for all of that.”

[scientificinquirer-blog]

The Big Picture: Star anise and its improbable connection with Tamiflu.

Star anise. (CREDIT: Retro Lenses) Star anise is a spice that comes from the fruit of the Illicium verum tree, a small evergreen native to Northeast Vietnam and South China. The spice is shaped like a star, with each “point” containing a seed. The fruit is harvested before ripening, dried, and used both for its flavor and medicinal properties. Star anise has a distinct, strong flavor similar to…

[chemxpert]

Chemxpert Database Insights : Navigating Global Pharmaceutical Growth

Explore the Chemxpert Database to uncover the latest insights on the global pharmaceutical industry growth rate and understand the impact of new rules for clinical trials in India. Delve into data on the top 10 pharmaceutical companies and learn about the biggest pharmaceutical companies shaping the market. With diverse types of data in the pharmaceutical industry, Chemxpert offers comprehensive analytics to keep you informed and competitive in this evolving field.