Medical

An ionic forcefield for nanoparticles

Published

4 years ago

December 6, 2020

Jean

Nanoparticles may have the solution to awful side effects from chemotherapy. If doctors can use nanoparticles to carry drugs directly to a specific part of the body, they can make chemotherapautics less toxic.

But it is not that simple. Because nanoparticles trigger the body’s immune system to fight against them, the vast majority of them never reach their target.

Human blood serum contains proteins that tag the nanoparticles as invadors and a paltry 1% of the nanoparticles get to where they are going.

“No one escapes the wrath of the serum proteins,” said Eden Tanner, who was a postdoctoral Bioengeneering fellow at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS).

A research team led by Tanner and Professor Samir Mitragotri have created an ionic forcefield that could enable nanoparticles to achieve their goal by preventing the proteins in the blood serum from tagging the nanoparticles.

In experimenting with mice, the researchers found that the could make the nanoparticles to survive longer in the human body using a coat of the ionic liquid. This coating increased the number of nanoparticles that reached their target from 1% to more than 50%.

“The fact that this coating allows the nanoparticles to slip past serum proteins and hitch a ride on red blood cells is really quite amazing because once you are able to fight the immune system effectively, lots of opportunities open up,” explained Mitragotri, who is part of the Harvard’s Wyss Institute for Biologically Inspired Engineering faculty.

Ionic liquids are liquid salts and they are capable of holding charge.

“We knew that serum proteins clear out nanoparticles in the bloodstream by attaching to the surface of the particle and we knew that certain ionic liquids can either stabilize or destabilize proteins,” said Tanner, an assistant professor of chemistry and biochemistry at the University of Mississippi. “The question was, could we leverage the properties of ionic liquids to allow nanoparticles to slip past proteins unseen.”

The great thing about ionic liquids is that every small change you make to their chemistry results in a big change in their properties,” explained Christine Hamadani, who was the first author and a former graduate student at SEAS. “By changing one carbon bond, you can change whether or not it attracts or repels proteins.”

At the moment, Hamadani is a graduate student based at Tanner’s lab in the University of Mississippi.

Researchers used choline hexenoate to coat the nanoparticles. It is an ionic liquid with a natural aversion to serum proteins. The nanoparticles coated with ionic liquid attached themselves to red-blood cells and remained in circulation until they got to the lungs.

“This hitchhiking phenomenon was a really unexpected discovery,” said Mitragotri. “Previous methods of hitchhiking required special treatment for the nanoparticles to attach to red blood cells and even then, they only stayed at a target location for about six hours. Here, we showed 50 percent of the injected dose still in the lungs after 24 hours.”

The scientists are yet to understand exactly why the nanoparticles so easily attached themselves to lung tissue, but it shows that the system can work with a fair amount of precision.

“This is such a modular technology,” said Tanner, who plans will go on with her research at University of Mississippi. “Any nanoparticle with a surface change can be coated with ionic liquids and there are millions of ionic liquids that can be tuned to have different properties. You could tune the nanoparticle and the liquid to target specific locations in the body.”

“We as a field need as many tools as we can to fight the immune system and get drugs where they need to go,” said Mitragotri. “Ionic liquids are the latest tool on that front.”

Morgan J. Goetz co-authored the research paper.

Medical

AI Breakthrough: New System Detects Early Signs of Heart Disease, Revolutionizing Preventive Care

Published

2 days ago

October 20, 2024

Jean

In a groundbreaking development that could transform the landscape of cardiovascular health, researchers have unveiled an innovative artificial intelligence system capable of detecting early signs of heart disease. This cutting-edge technology, detailed in a recent study published in the Journal of Medical AI, analyzes routine medical tests to identify potential cardiac issues long before they manifest as serious health problems.

Heart disease remains the leading cause of death in the United States, claiming one life every 33 seconds. With over 700,000 deaths attributed to cardiovascular diseases in 2022 alone, the need for early detection and intervention has never been more critical. This new AI system represents a significant step forward in addressing this pressing health concern.

The AI-powered diagnostic tool, developed by a team of researchers from the National Institute of Cardiovascular Health, utilizes machine learning algorithms to analyze a combination of standard blood tests, electrocardiograms (ECGs), and patient history data. By identifying subtle patterns and markers that might escape human observation, the system can predict the likelihood of developing heart disease with remarkable accuracy.

Dr. Sarah Chen, the lead researcher on the project, explained, “Our AI system is designed to detect the earliest signs of cardiovascular issues, often years before a patient might experience symptoms. This early warning system could potentially save countless lives by allowing for timely interventions and lifestyle changes.”

The system’s effectiveness was demonstrated in a large-scale clinical trial involving over 50,000 participants across diverse demographic groups. Results showed that the AI tool was able to identify individuals at high risk of developing heart disease with an accuracy rate of 92%, significantly outperforming traditional risk assessment methods.

One of the key advantages of this new technology is its ability to integrate seamlessly into existing healthcare workflows. The American Heart Association has long advocated for improved early detection methods, and this AI system aligns perfectly with that goal. By utilizing data from routine medical tests, the system can be implemented without requiring additional, costly procedures or specialized equipment.

Dr. Michael Rodriguez, a cardiologist not involved in the study, commented on the potential impact: “This AI system could revolutionize how we approach cardiovascular health. By identifying at-risk patients earlier, we can implement preventive measures more effectively, potentially reducing the incidence of heart attacks and strokes.”

The implications of this technology extend beyond individual patient care. Health economists project that widespread adoption of this AI system could lead to significant cost savings in healthcare. By shifting the focus to prevention and early intervention, the system could help reduce the enormous financial burden associated with treating advanced heart disease, which currently costs the U.S. healthcare system over $250 billion annually.

However, as with any new medical technology, there are challenges to overcome. Privacy concerns and the need for robust data protection measures are at the forefront of discussions surrounding the implementation of AI in healthcare. The researchers behind the system emphasize their commitment to maintaining patient confidentiality and adhering to strict ethical guidelines in the use of medical data.

The National Institute of Health has expressed interest in the potential of this AI system and is currently reviewing proposals for larger-scale trials. If these trials prove successful, the technology could be rolled out to hospitals and clinics nationwide within the next few years.

The development of this AI system is part of a broader trend of technological innovation in healthcare. From wearable devices that monitor vital signs to advanced imaging techniques, the integration of technology is reshaping how we approach disease prevention and treatment.

Dr. Chen and her team are already looking to the future, exploring ways to expand the capabilities of their AI system. “We’re investigating the possibility of adapting our algorithms to detect other types of cardiovascular issues, such as arrhythmias and valve disorders,” she said. “The potential applications of this technology are vast.”

As the medical community continues to grapple with the challenges of heart disease, innovations like this AI system offer hope for a future where cardiovascular health can be managed more proactively and effectively. By harnessing the power of artificial intelligence, we may be on the cusp of a new era in preventive cardiology, one that could save millions of lives and improve the quality of life for countless individuals at risk of heart disease.

The journey from laboratory breakthrough to widespread clinical application is often long and complex, but the potential benefits of this AI system are clear. As further research is conducted and the technology is refined, it may well become an indispensable tool in the fight against one of the world’s most pervasive and deadly health threats.

In the coming years, as this AI system and similar technologies continue to evolve, they promise to reshape our approach to cardiovascular health, offering a future where heart disease can be identified and addressed long before it becomes life-threatening. This represents not just a technological achievement, but a beacon of hope for millions of people around the world at risk of heart disease.

Medical

AI Breakthrough: New Model Revolutionizes Protein Structure Prediction

Published

3 weeks ago

September 29, 2024

Jean

In a groundbreaking development, researchers have unveiled a new artificial intelligence model that promises to revolutionize the field of protein structure prediction. This cutting-edge AI system has demonstrated unprecedented accuracy in determining the three-dimensional shapes of proteins, a feat that could accelerate drug discovery and deepen our understanding of fundamental biological processes.

The new model, developed by a team of international scientists, builds upon the success of previous AI-driven approaches like AlphaFold and RoseTTAFold. These earlier systems had already made significant strides in tackling the protein folding problem, a challenge that has puzzled scientists for over half a century. However, the latest innovation takes protein structure prediction to new heights, offering a level of precision that was previously unattainable.

Proteins, the building blocks of life, perform a vast array of functions in living organisms. Their functionality is intimately tied to their three-dimensional structure, which has traditionally been determined through complex and time-consuming experimental methods such as X-ray crystallography and cryo-electron microscopy. The ability to accurately predict these structures from amino acid sequences alone has long been a holy grail in structural biology.

The new AI model employs advanced machine learning techniques, including deep neural networks and attention mechanisms, to analyze vast amounts of genomic and proteomic data. By leveraging evolutionary information and physical principles, the system can infer the most likely structural configuration of a given protein sequence.

Dr. Sarah Chen, lead researcher on the project, explained, “Our model doesn’t just predict the overall fold of a protein; it can pinpoint the positions of individual atoms with remarkable accuracy. This level of detail is crucial for understanding protein function and for designing drugs that can interact with specific molecular targets.”

The implications of this breakthrough are far-reaching. In the field of drug discovery, accurate protein structure predictions can significantly accelerate the process of identifying potential therapeutic compounds. By simulating how different molecules interact with target proteins, researchers can narrow down candidates for experimental testing, potentially saving years of laboratory work and billions of dollars in development costs.

Moreover, the new model’s capabilities extend beyond single proteins to complex molecular assemblies. Dr. Chen noted, “We’ve seen promising results in predicting the structures of protein complexes and even how proteins interact with DNA and RNA. This opens up new avenues for understanding cellular machinery at an unprecedented level of detail.”

The biotechnology industry has already taken notice of this development. Several pharmaceutical companies have expressed interest in incorporating the new AI model into their drug discovery pipelines. Dr. Michael Patel, Chief Scientific Officer at Innovex Pharmaceuticals, commented, “This technology has the potential to transform how we approach drug design. We’re particularly excited about its applications in developing treatments for diseases involving hard-to-target proteins.”

In the realm of basic science, the model is expected to accelerate research across various disciplines. Structural biologists can use the predictions to guide their experimental work, while biochemists and molecular biologists can gain new insights into protein function based on structural information.

The environmental sciences may also benefit from this breakthrough. Understanding the structures of enzymes involved in biodegradation could lead to more effective strategies for breaking down pollutants or developing sustainable materials.

Despite the enthusiasm, experts caution that the new AI model is not a complete replacement for experimental methods. Dr. Lisa Wong, a structural biologist at the National Institute of Health Sciences, emphasized, “While these predictions are incredibly valuable, they still need to be validated experimentally. The AI model is a powerful tool, but it’s part of a larger toolkit that includes traditional structural biology techniques.”

The development of this AI model also raises important questions about data sharing and accessibility in scientific research. The team behind the innovation has committed to making their model openly available to the scientific community, following in the footsteps of initiatives like the AlphaFold Protein Structure Database.

As the field of AI-driven protein structure prediction continues to advance, it’s clear that we are entering a new era in structural biology and drug discovery. The ability to rapidly and accurately determine protein structures has the potential to accelerate scientific progress across multiple disciplines, from fundamental research to applied biotechnology.

Looking ahead, researchers are already exploring ways to further enhance the model’s capabilities. Future developments may include the ability to predict dynamic protein movements, simulate large-scale molecular interactions, and even design novel proteins with specific functions.

The impact of this breakthrough extends beyond the scientific community. As our understanding of protein structures grows, it could lead to more personalized medical treatments, more efficient industrial processes, and novel solutions to global challenges in health and the environment.

In conclusion, the unveiling of this new AI model for protein structure prediction marks a significant milestone in the intersection of artificial intelligence and biology. As we continue to unlock the secrets of life’s molecular machinery, we edge closer to a future where the complexities of the protein world are no longer a barrier but a gateway to innovation and discovery.

Medical

WHO Unveils Health Technology Access Pool: A New Era for Global Health Equity

Published

3 months ago

July 29, 2024

Jean

In a landmark move to address global health disparities, the World Health Organization (WHO) has announced the launch of the Health Technology Access Pool (HTAP). This initiative, set to officially commence in the second quarter of 2024, aims to revolutionize access to essential health technologies worldwide, building upon the lessons learned from its predecessor, the COVID-19 Technology Access Pool (C-TAP).

The HTAP represents a significant evolution in WHO’s approach to health technology access, expanding its scope beyond pandemic response to encompass a broader range of public health priorities. Dr. Tedros Adhanom Ghebreyesus, WHO Director-General, emphasized the initiative’s importance, stating, “Equitable access to essential health products is an essential part of universal health coverage, and of global health security.”

At its core, HTAP seeks to facilitate the sharing of intellectual property, knowledge, and data among technology developers, manufacturers, and health organizations. This collaborative approach aims to accelerate innovation and expand global production capacity for critical health technologies. The initiative’s expanded focus includes not only pandemic preparedness but also addresses other pressing public health concerns, targeting platform technologies and health products relevant both during and between health emergencies.

One of the key strengths of HTAP lies in its comprehensive engagement across the entire technology value chain. This holistic approach considers the various steps and support required to transform licensed technologies into sub-licensed, quality-assured products with viable market potential. By doing so, HTAP aims to enhance the attractiveness of licensed technologies to recipient manufacturers, offering greater market opportunities and financial sustainability in non-pandemic periods.

The initiative’s strategy is built around fostering partnerships across the value chain, from research institutions to manufacturers and end-users. This collaborative model is designed to ensure the successful implementation of HTAP and address access gaps on an ongoing basis. WHO plans to provide further details on HTAP’s operations and targeted technologies in the first quarter of 2024, with the official launch tentatively scheduled for the second quarter.

HTAP’s approach represents a significant departure from its predecessor, C-TAP, which was launched in May 2020 in collaboration with the Government of Costa Rica and other partners. While C-TAP focused primarily on facilitating access to COVID-19 health products, HTAP expands its purview to future emergencies and other priority diseases. This expansion is coupled with a more proactive approach, full integration within the access ecosystem, and alignment with existing WHO programs.

The initiative also adopts a nuanced approach to licensing, recognizing the need for differentiated strategies when dealing with mature health products versus upstream technologies. This flexibility allows HTAP to work with technology holders and partners on tailored technology transfer implementation strategies, taking into account market dynamics and potential saturation.

HTAP’s potential impact on global health equity is significant, particularly for regions like Africa that have historically faced challenges in accessing cutting-edge health technologies. Dr. Ahmed Ogwell, Africa CDC’s deputy director, hailed the platform as “urgently needed” to bridge the existing technology development gap. He emphasized the potential for HTAP to be a game-changer for the African continent and other parts of the world where technological development lags behind the West.

The initiative’s voluntary nature allows countries to leverage useful technologies as soon as they become available. However, Dr. Ogwell also acknowledged the uncertainty surrounding whether those possessing highly sought-after technologies would willingly share their products on the platform. Despite this challenge, he remains optimistic that HTAP, based on agreed parameters, will encourage voluntary contributions of intellectual property rights and knowledge to the platform.

To ensure its success, HTAP will harness and align WHO resources, leveraging the necessary expertise and programs in setting priorities, developing enabling policies, and providing support over the value chain. This approach extends to partnerships with external entities that form part of the larger health product access ecosystem.

The WHO is also focusing on building the infrastructure and governance structure necessary for HTAP’s success. This includes staffing senior dedicated positions to manage and monitor HTAP’s performance, establishing a WHO-led steering group with defined purposes, and implementing an evaluation framework to measure success. The development and publication of clear operating procedures, guidance, and advocacy materials will be critical to HTAP’s launch and ongoing operations.

As the world continues to grapple with health inequities exposed and exacerbated by the COVID-19 pandemic, initiatives like HTAP offer a beacon of hope. By promoting continuity and alignment along the value chain, HTAP seeks to achieve sustainable success in improving global health outcomes. The initiative’s focus on equitable access to health technologies could play a crucial role in advancing universal health coverage and strengthening global health security.

However, the success of HTAP will largely depend on the willingness of technology holders to participate and the ability of recipient countries to absorb and utilize the shared technologies effectively. As Dr. Ogwell pointed out, African countries and other developing nations must ramp up investments in their health sectors to fully benefit from this initiative.

As we approach the official launch of HTAP, the global health community watches with anticipation. If successful, this initiative could mark a significant step forward in addressing health disparities and ensuring that life-saving technologies reach those who need them most, regardless of geographical or economic barriers.

The Health Technology Access Pool represents a bold vision for a more equitable global health landscape. By learning from past experiences and adopting a more comprehensive, proactive approach, WHO aims to create a sustainable model for technology sharing that could revolutionize how we address global health challenges. As the world continues to face both known and unforeseen health threats, initiatives like HTAP may prove crucial in building a more resilient and equitable global health system for all.