Note: In the context of this edition of the Tulane Digest and biomedical research, there is an operational distinction between the terms of “sex” and “gender.” “Gender” refers to socially constructed roles, behaviors, expression, and identity. “Sex-based” biology and medicine focus on sex assigned at birth through anatomical, chromosomal or other features. While the interaction between sex, gender, and other identity factors and their impact on health over the course of human life is complex topic requiring dedicated research in the pursuit of health equity, we maintain the narrow definition of biological sex for the scope of this article.

Slipping through the cracks: A continued lack of women in biomedical research

Female biology has long been underrepresented or downright ignored in both basic and clinical biomedical research, with researchers citing reasons such as increased variability in female biological and behavioral responses due to hormonal changes—since disproven in various studies including a meta-analysis of over 300 neuroscience articles—and claims that drugs in early development might harm fertility, despite estimates that the total number of pregnant individuals taking either prescribed or over-the-counter (and often necessary) medications is well over 50%. Though the FDA and NIH have in the past few decades released guidelines and mandates for inclusion of females in clinical trials and basic research, women are still routinely underrepresented in early-stage clinical trials. Even though female non-human animals are now often included in preclinical biomedical experiments, many of these are not followed-up with a proper statistical analysis, nearly negating the reason for their inclusion in the first place.

As a result of these persistent integration failures, women continue to find themselves navigating a healthcare system that does not fully understand their biology, despite observed differences in cardiovascular diseases, Alzheimer’s prevalence, schizophrenia, drug pharmacokinetics; even baseline metrics commonly taken for granted such as normal blood pressure range have recently been observed to differ in women. Furthermore, the hormonal changes of menopause have been shown to alter areas from cardiovascular health to cognition for reasons that are separate from changes purely due to age. At the same time, menopause appears to accelerate cellular aging.  These findings produce further complications for ongoing clinical studies of women’s health over the course of their lifespans. Still, a greater effort to include women in clinical trials has the potential to produce more efficient studies and greater likelihood of long-term drug success. An FDA report found that eight of the ten drugs withdrawn from market between 1997 and 2000 (in some cases, within only a few years of approval) showed higher risk to women. A more rigorous analysis of adverse events and consideration of potential sex-based prescription frequencies could have ended trials earlier in the pipeline, saving considerable expenditure. Some studies find that women are more likely to complete clinical trials, leading to superior retention, greater statistical power, and the potential for shorter time to trial completion.

Even with proper inclusion and analysis, the complexity of interacting sex-related variables and their changes over time have the potential to cause difficulty when crafting accurate and effective research and healthcare strategies to address the unique needs of women. However, institutions are taking heed. The NIH’s All of Us program aims to capture health differences and disparities across the whole spectrum of diverse individuals across the US, and is committed to advancing women’s health research. Tulane University’s Center of Biomedical Research Excellence in Sex-based Precision Medicine is dedicated to conducting projects at the intersection of sex, gender and other genetic, biological, and social factors of health. At Mayo Clinic, the Women’s Health Research Center focuses on advancing sex-based studies and training early researchers in intersectional women’s health research through its BIRCWH program, one of 19 across the nation.

Artificial intelligence as a path to greater fairness in healthcare

In addition to dedicated research, addressing these complex issues requires innovative solutions, and recent advances in artificial intelligence (AI) may help to provide answers. The continued development of AI and machine learning—which have already made great strides in medicine, from evaluating chest X-rays to designing a drug for idiopathic pulmonary fibrosis that reached clinical trials—gives promise for better, less-biased detection of sex-based differences in biology. When trained on vast amounts of appropriate data, AI models are able to detect patterns and relationships in large, complex datasets that might otherwise be invisible to humans. Such models can detect genetic disorders through subtle differences in facial structure or determine how an individual’s cancer evolved, potentially allowing prediction of disease progression.

Within the realm of sex-based biology, artificial intelligence has already shown success. A study using AI found sex-based differences in posture, with potential to guide screening and treatment in physical therapy and sports medicine. Another recent study led by researchers at NYU Langone Health found sex differences in white matter of the brain at the microstructural level, potentially providing insight into why psychiatric and neurological disorders sometimes present differently between men and women. Researchers at the Karolinska Institute in Sweden used AI to find sex-specific gene expression patterns related to calcification of the aortic valve of the heart during aortic stenosis, offering a path toward precision therapies. Within the clinic, properly-trained AI-powered technologies such as ambient clinical documentation or large language model-assisted diagnostics could increase sex health equity by ensuring that symptoms are documented and properly considered, given that women’s health concerns are unfortunately more frequently dismissed by doctors compared with those of men. 

Those who forget the past: Avoiding AI’s potential pitfalls

Despite great promise, it must also be stated that care must be taken when employing such models.  Otherwise, they have the capacity to continue to perpetuate (and even amplify) historical biases against women and other underrepresented groups. An AI model trained on datasets that do not properly incorporate sex as a biological variable may do more harm than good. A recent study examined whether OpenAI’s GPT-4 encoded racial and sex biases in areas such as diagnostic reasoning and clinical plan generation, and found that it did not appropriately account for demographic diversity and tended to overrepresent stereotypes of diseases based on race and sex. If a model is trained on medical texts and diagnoses that were often based on decades of data ignoring sex as a biological variable, it will make many of the same mistakes of the humans who produced that data. But once this is recognized, and after applying more careful algorithm design and a commitment to undoing previous discrimination in medicine, AI systems hold great potential for parsing out sex differences (as well as a plethora of other critical factors impacting health) and ushering in greater health equity for women.

The beginnings of a new era in health equity

Because the dangers are being recognized, discussed and beginning to be addressed, we now have room for cautious optimism. Technological advancements combined with greater awareness of sex-based health inequity at both the level of individual researchers and the US government are adding velocity to a momentum that has been building over the past decades. Through greater outreach to women for inclusion in clinical trials, more careful inclusion of sex as a biological variable in basic research (and appreciation of its value even when a study does not explicit aim to research sex differences), and a commitment to better health care policies and access for women, we have more power than ever before to bring about change and ensure a more equitable future.

____________________________________________________

The Tulane Medicine team, who is also the Tulane Digest Team, is partnering at BIO 2024this week. You can send a request through the BIO partnering system, or email us directly to arrange a time to connect.

____________________________________________________

Recent Podcast Episode Drops:

Whether for travel entertainment or a quick listen between meetings, check out 6 recently released bite-size episodes of BIO from the BAYOU. Check them out on the BftB Website, Apple Podcasts, Spotify, or anywhere you podcast.

____________________________________________________ 

Share the Science: Please forward this issue and encourage others to sign up for Tulane School of Medicine’s Digest Mailing List.

____________________________________________________ 

Curated Research and Research-Related News Summaries, Analyses, and Syntheses. Published on behalf of The Tulane University School of Medicine. Content is generated by reviewing scientific papers and preprints, reputable media articles, and scientific news outlets.  We aim to communicate the most current and relevant scientific, clinical, and public health information to the Tulane community – which, in keeping with Tulane’s motto, “Not for Oneself but for One’s Own”, is shared with the entire world.

Alexis L. Ducote, PhD: Editor-in-Chief

Special thanks to James Zanewicz, JD, LLM, RTTP and Elaine Hamm, PhD for copy-editing assistance.

Antibiotics: In Search of the Next Wonder Drug

In a world full of discussions around AI, gene therapy and robotic surgery, antibiotics may seem like relics of early medicine, but their pivotal role in modern healthcare cannot be overstated. In 1900, pneumonia, tuberculosis, enteritis, and diphtheria caused a third of all deaths, especially among children under 5. Early 20^th century advancements in infection prevention such as surgical asepsis and water chlorination improved public health, but treatments were still limited. Existing “cures” like salvarsan and malariotherapy often had severe side effects and were only effective against a limited array of pathogens. This changed in 1928 with Alexander Fleming’s discovery of penicillin leading to the “golden age of antibiotic discovery” from around 1940 to 1960, during which numerous new antibiotics were developed.

The Snake that Ate Its Own Tail: Antibiotic Overuse Creates Resistance

As the field of antimicrobials was evolving, so were the bacteria, spurring an arms race between medical science and microbial adaptation in the form of antimicrobial resistance (AMR). Through genetic mutations and the exchange of resistance genes, bacteria can develop mechanisms to evade the effects of antibiotics and render existing treatments less effective. As an example, many antibiotics – including penicillin and its derivatives – exhibit a chemical structure characterized by a beta-lactam ring (in red).

This is important, as this structure reacts with components of the bacterial cell wall to, quite simply, destroy it. In response to widespread use of beta-lactam antibiotics, bacteria have developed enzymes called beta-lactamases, which cut open the ring before the antibiotic can exert its effect. Bacteria may also utilize efflux pumps to simply remove the drug from the cell before it kills them. As one class of antibiotic loses efficacy and another is brought in to take its place, pathogens may develop multidrug resistance. The World Health Organization (WHO) has identified antibiotic resistance as one of the biggest threats to global health today, with the potential to negate many of the gains of modern medicine over the past century.

Make New Friends, but Keep the Old: Innovative Strategies against AMR

In response to this threat, researchers are employing several innovative strategies to combat antimicrobial resistance (AMR). One approach involves the development of combination drug regimens to directly fight existing resistance mechanisms. One such method—currently being developed by groups such as the US company VenatoRx and researchers at the University of Tunis El Manar—is the use of beta-lactamase inhibitors to specifically target and disrupt the bacterial enzymes which provide resistance against existing antibiotics. Another tactic is phage therapy, which uses bacteriophages to infect and kill bacteria. The Biomedical Advanced Research and Development Authority (BARDA) recently awarded $23.9 million to US company Locus Biosciences, Inc. to continue development of a phage therapy against urinary tract infections caused by drug-resistant E. coli. Meanwhile, Tulane University’s Wimley Lab is developing potent antimicrobial peptides as alternatives to traditional antibiotics. These peptides attack bacterial membranes without requiring specific binding structures, making development of resistance much more difficult. Furthermore, different therapies are contemplated being used in combinations that will hit pathogens through multiple mechanisms, greatly decreasing the chance of their survival and pushing back any ability to development longer-term resistance.

Economic Challenges in Antibiotic Development

Despite significant progress in development of new antimicrobial treatments, bringing a therapy through trials and to patients faces significant challenges due to economic and systemic hurdles. The antibiotic business model is considered broken, primarily because the costs of development are not matched by the financial returns. Governments and organizations are beginning to recognize the gravity of antimicrobial resistance, which could cause 10 million deaths annually by 2050, and are exploring alternative funding models and incentives to stimulate antibiotic research and development. Despite initiatives like GARDP and CARB-X, which aim to accelerate the development of new antibiotics, the current efforts have been deemed insufficient by experts and the World Health Organization. Most new drugs are simply derivatives of existing classes.  This means they arrive on the scene with limited efficacy against resistant strains, and so the global antibiotic pipeline remains underfilled of truly novel and effective solutions. The economic reality is stark: it costs up to $1.5 billion to develop a new antibiotic, but the median sales in the U.S. are only about $16.2 million. This discrepancy highlights the need for a restructured economic approach that not only fosters innovation but also makes the antibiotic market viable and attractive for pharmaceutical companies. A new initiative laid out in the UK hopes to tackle this by introduction of a subscription model and 5-year plan to fund the development of new antimicrobials while slowing further development of resistance. This model would pay pharmaceutical companies a fixed annual fee based on the value of the antimicrobials to the NHS, rather than the volume sold, reducing the incentive for overuse. Meanwhile, in 2023, a group of U.S. Senators and Representatives from both parties reintroduced the Pioneering Antimicrobial Subscriptions to End Upsurging Resistance (PASTEUR) Act in order to drive development of novel antimicrobials and antibiotics.  However, enough bipartisan agreement has not been fully reached for the act to pass and become mandate.

Fostering Global Cooperation to Combat AMR

Overall, stopping the spread of AMR will require a coordinated global effort between governments, clinicians and the biotech industry. Some of the key strategies include the 1) implementation of robust antimicrobial stewardship programs to ensure the rational use of antibiotics and 2) development of truly novel antimicrobials and rapid diagnostics. The One Health approach, aimed at addressing the interconnectedness of human, animal, and environmental health, will be crucial for managing AMR by reducing inappropriate antimicrobial use across all sectors and improving areas adjacent to treatment itself such as hygiene, infection control, and waste management. The development of enhanced surveillance systems is necessary to begin to monitor antibiotic use and resistance patterns, as this information will inform both public policy decisions and regulatory actions. Additionally, accessible public education and awareness campaigns will be help promote a more responsible antibiotic use and prevent infections. A concerted effort from governments, healthcare providers, researchers, and other stakeholders is critical to mitigate the global health crisis posed by AMR and to prevent a return to a pre-antibiotic era that is now dominated not by more mundane infections, but by true super-bugs capable of causing a wave of global pandemics.

 ____________________________________________________

The Tulane Medicine team, who is also the Tulane Digest Team, is partnering at BIO 2024 this week. You can send a request through the BIO partnering system, or email us directly to arrange a time to connect.

____________________________________________________

Recent Podcast Episode Drops:

Whether for travel entertainment or a quick listen between meetings, check out 6 recently released bite-size episodes of BIO from the BAYOU. Check them out on the BftB Website, Apple Podcasts, Spotify, or anywhere you podcast.

____________________________________________________ 

Share the Science: Please forward this issue and encourage others to sign up for Tulane School of Medicine’s Digest Mailing List.

____________________________________________________ 

Curated Research and Research-Related News Summaries, Analyses, and Syntheses. Published on behalf of The Tulane University School of Medicine. Content is generated by reviewing scientific papers and preprints, reputable media articles, and scientific news outlets.  We aim to communicate the most current and relevant scientific, clinical, and public health information to the Tulane community – which, in keeping with Tulane’s motto, “Not for Oneself but for One’s Own”, is shared with the entire world.

Alexis L. Ducote, PhD: Editor-in-Chief

Special thanks to James Zanewicz, JD, LLM, RTTP and Elaine Hamm, PhD for copy-editing assistance.

Imagine a world where clinical trials could operate with speed, efficiency, precision, and personalized approaches. This transformative vision is becoming a reality as AI integrates into the clinical trial landscape, offering solutions to long-standing challenges and paving the way for groundbreaking advancements in medical research. By harnessing the capabilities of machine learning, big data analytics, and predictive modeling, AI is optimizing trial processes and enhancing the overall quality and speed of drug development​​.

The traditional clinical trial process is labor-intensive, expensive, and often slow, with an average duration of several years and costs soaring into the millions. One of the critical pain points in clinical trials is patient recruitment and retention. According to the University of Mississippi Medical Center, nearly 80% of all clinical trial sites in the US fail to meet their enrollment targets, leading to significant delays and escalated costs. Additionally, data analysis within trials is mostly manual and error-prone, with researchers grappling to process and interpret vast amounts of complex data. These inefficiencies are exacerbated by rigid trial designs that do not account for patient variability, resulting in suboptimal treatment protocols and frequent amendments that further extend timelines, inflate budgets, and result in failed outcomes.

AI in Healthcare: The Ultimate Patient Whisperer

One of the primary applications of AI in clinical trials is patient recruitment. AI algorithms can analyze large datasets, including electronic health records (EHRs), genetic information, and clinical notes, to identify suitable trial candidates. Companies like Deep 6 AI are revolutionizing this space with platforms utilizing natural language processing and machine learning to rapidly scan millions of patient records. This approach can match potential participants with desired criteria in a fraction of the time required by traditional methods, ensuring that trials can recruit a diverse and representative patient population. Researchers at Cincinnati Children’s Hospital Medical Center also developed a natural language processing and machine learning-based system, the Automated Clinical Trial Eligibility Screener (ACTES), to analyze structured and unstructured data in an Emergency Department setting. The tool successfully reduced patient screening time for clinical research coordinators by 34% and increased overall enrollment rates by 11.1%. By automating time-consuming and high-cost components of the recruitment process, AI accelerates trial initiation and enhances the likelihood of finding eligible participants who meet specific trial requirements.

Retaining participants throughout the duration of a clinical trial is equally challenging. AI can significantly enhance patient engagement and adherence through continuous monitoring using wearable devices and mobile health applications. These tools collect real-time data on patient behavior, symptoms, and medication adherence, allowing researchers to identify and address issues proactively. Several innovative examples of combining wearable devices and AI to enhance trial engagement have been demonstrated in Tulane’s Research Innovation for Arrhythmia Discovery Center. In the iPredict, Prevent study, researchers are working to evaluate the progression of atrial myopathy using biometric data, including volume changes in blood vessels, heart rate, and oxygen saturation. Using this data, the researchers aim to train a machine learning algorithm to predict cardiovascular outcomes and enable earlier interventions. In trials with low patient engagement, AI can also analyze engagement patterns and predict when a participant is at risk of dropping out. By ensuring consistent engagement and adherence, AI helps maintain the integrity of the trial data, leading to more reliable and valuable outcomes.

From Slow and Methodical to Dynamic: How AI Adds Jazz to Clinical Trials

The use of AI has opened new opportunities in designing personalized treatment plans and adaptive trial protocols. Researchers at Brigham and Women’s Hospital and Harvard T.H. Chan School of Public Health highlight that adaptive trials allow for prospectively planned changes to a trial, enhancing flexibility and responsiveness based on accumulating data. To properly utilize patient results and customize interventions, AI can process and analyze real-time data based on individual patient characteristics. AI algorithms identify subpopulations within a trial that respond differently to treatments, allowing for more targeted therapeutic approaches and reducing the number of patients in poorly performing treatment groups. This level of precision and adaptability can lead to better patient outcomes and a higher likelihood of trial success. It is important to note that the use of adaptive trials will require careful consideration of statistical validity and development of regulatory guidelines.

Several industry use cases further underscore the transformative potential of AI in clinical trial design. For instance, Unlearn.AI leverages digital twins—virtual models of patients created from historical data—to simulate trial outcomes and optimize designs. The use of digital twins has reduced the reliance on control groups and accelerated trial timelines. Unlearn’s study on Alzheimer’s Disease demonstrated that digital twins showed value in predicting clinical outcomes, allowing for a reduction in the number of required subjects by up to 35% for control arms and 21% for the overall study size. The AI-based digital twin methodology shortens trial duration while cutting down on costs and enhancing efficiency. Additionally, digital twins adhere to regulatory guidelines, ensuring that the accelerated timelines and reduced control group sizes do not sacrifice the reliability of traditional clinical trials.

 The Red Tape Tango: AI’s Dance with Regulations

While the use of AI in clinical trials shows significant promise, these innovations also highlight the growing need to address regulatory challenges. Traditional trial frameworks were not designed with AI in mind, leading to uncertainties around data privacy, algorithm transparency, and validation requirements. Ensuring that AI systems are transparent, and their decisions are explainable is crucial for maintaining the trust and ethical standards required for clinical trials. The absence of standardized guidelines complicates the regulatory landscape, making it difficult for sponsors and researchers to navigate the approval processes. Regulators across the EU, US, and UK are starting to acknowledge the urgency with which regulation is needed, and in May 2023, the FDA released a discussion paper soliciting feedback on the use of AI/ML in drug development. Addressing these regulatory challenges is paramount to fully capitalize on the benefits of AI in clinical trials.

Further collaboration between regulators, researchers, and AI developers can create a more conducive environment for innovation while ensuring patient safety and data integrity. Organizations like the Alliance for Artificial Intelligence in Healthcare (AAIH) are actively working towards establishing such standards. By working to establish clear guidelines and promoting dialogue among stakeholders, the AAIH seeks to ensure that AI is integrated safely and effectively across clinical trials and healthcare, benefiting patients and advancing medical research.

 AI’s Encore Performance

AI stands at the forefront of a paradigm shift in clinical trials, with the promise of enhancing efficiency and effectiveness. AI-driven tools can streamline data analysis, optimize patient recruitment, and enable adaptive trial designs more responsive to patient needs. Machine learning algorithms can sift through extensive datasets, identifying patterns and making predictions that inform more precise and personalized treatment plans. In addition, we need to keep an eye on ethical and community-focused adoption of AI.  To reach these goals, collaborative efforts and ongoing dialogue between stakeholders will be key to overcoming regulatory challenges and driving innovative and effective healthcare solutions – and active engagement in organizations like the Alliance for Artificial Intelligence in Healthcare will be crucial to facilitating productive outcomes.

____________________________________________________

The Tulane Medicine team, who is also the Tulane Digest Team, is partnering at BIO 2024 this week. You can send a request through the BIO partnering system, or email us directly to arrange a time to connect.

____________________________________________________

Recent Podcast Episode Drops:

Whether for travel entertainment or a quick listen between meetings, check out 6 recently released bite-size episodes of BIO from the BAYOU. Check them out on the BftB Website, Apple Podcasts, Spotify, or anywhere you podcast.

____________________________________________________ 

Share the Science: Please forward this issue and encourage others to sign up for Tulane School of Medicine’s Digest Mailing List.

____________________________________________________ 

Curated Research and Research-Related News Summaries, Analyses, and Syntheses. Published on behalf of The Tulane University School of Medicine. Content is generated by reviewing scientific papers and preprints, reputable media articles, and scientific news outlets.  We aim to communicate the most current and relevant scientific, clinical, and public health information to the Tulane community – which, in keeping with Tulane’s motto, “Not for Oneself but for One’s Own”, is shared with the entire world.

Eric Malamud, MBA, and Alexis L. Ducote, PhD: Editors-in-Chief

Special thanks to James Zanewicz, JD, LLM, RTTP and Elaine Hamm, PhD for copy-editing assistance.

Inhale, exhale: Life with interstitial lung disease

Imagine taking a breath and feeling your lungs fill with ease – a simple action we often take for granted, save for the occasional respiratory infection. But what if every single breath became a struggle, feeling like you were trying to draw air in through a tiny straw? This is the reality for the many individuals living with interstitial lung diseases (ILDs). These conditions, which lead to progressive scarring of lung tissue, make it increasingly difficult to breathe. Though they might not make headlines as frequently as diseases such as cancer or neurodegeneration, ILDs are widespread and significantly impact the lives of the nearly 5 million individuals they are estimated to affect worldwide.

A needle in a haystack: The diagnostic difficulty of ILDs

The category of interstitial lung diseases represents a diverse group of more than 200 lung disorders that primarily affect the lung’s interstitium, the tissue and space between air sacs of the lungs and the blood vessels which absorb oxygen for delivery to the rest of the body and deposit carbon dioxide back into the lungs for exhalation. Unlike other lung diseases that may affect the airways or blood vessels, ILDs are characterized by inflammation, scarring (fibrosis), and stiffening of the lung tissue, which can lead to severe breathing difficulties, chronic cough, impaired oxygen transfer, and constant fatigue. Despite their shared features, ILDs vary widely in their causes, clinical presentations, and outcomes. Some ILDs are idiopathic (meaning their cause is unknown), while others are linked to environmental exposures, medications, or underlying autoimmune diseases. Common types of ILDs include idiopathic pulmonary fibrosis (IPF), hypersensitivity pneumonitis, and sarcoidosis, each with distinct pathological and clinical characteristics. Identifying and understanding these differences is a crucial component of accurate diagnosis and effective treatment.

To untangle the knot, or slice clean through

Clinicians differentiate between various interstitial lung diseases through a comprehensive, multidisciplinary approach that integrates clinical, radiologic, and histopathologic data. The initial diagnostic step involves composing a detailed patient history, including occupational and environmental exposures, smoking habits, and drug use, which can help identify common causes like pneumoconiosis, drug-induced ILD, and hypersensitivity pneumonitis. High-resolution computed tomography (HRCT) of the chest is an often-employed diagnostic tool, capable of identifying definitive patterns indicative of idiopathic pulmonary fibrosis such as usual interstitial pneumonia. Serologic tests can identify connective tissue disease-associated ILDs, while bronchoalveolar lavage and lung biopsies, including transbronchial and video-assisted thoracoscopic biopsies, provide histological confirmation. The final diagnosis is typically made through a multidisciplinary discussion involving pulmonologists, radiologists, and pathologists, ensuring that clinical, radiologic, and histopathologic findings are properly interpreted.

Given the complexity of diagnosis of ILDs, the establishment of specialized centers for pulmonary fibrosis has been instrumental in improving patient outcomes and advancing the understanding of these debilitating diseases. The Pulmonary Fibrosis Foundation (PFF) has been at the forefront of this effort with the PFF Care Center Network (CCN), which it established in 2013. The network ensures that patients with pulmonary fibrosis have access to experienced medical professionals and comprehensive support services. The CCN has expanded to include 88 centers across the country, combining expertise in patient care and research. These centers work collaboratively to provide early diagnosis, cutting-edge treatments, and enhanced awareness of pulmonary fibrosis. Across the US, clinicians at institutions from UCSF Health in San Francisco to Tulane University’s Interstitial Lung Disease Center in New Orleans engage in clinical trials dedicated to advancing treatments for patients suffering from ILDs. Additionally, the network plays a vital role in facilitating research and advocating for the pulmonary fibrosis community, aiming to expedite scientific discoveries, develop effective therapies and ensure patient engagement in the process.

Current treatments for interstitial lung diseases include a variety of pharmacologic and non-pharmacologic strategies. Immunosuppressive agents such as corticosteroids, cyclophosphamide, mycophenolate mofetil, and azathioprine are commonly used, particularly in connective tissue disease-associated ILD. Approved in 2014, the antifibrotic agents nintedanib and pirfenidone have shown efficacy in slowing disease progression, especially in idiopathic pulmonary fibrosis and systemic sclerosis-associated ILD. Biologic therapies, including tocilizumab, have also been approved for specific ILD subtypes. But non-pharmacologic treatments, such as supplemental oxygen and cardiopulmonary rehabilitation, are just as integral to a comprehensive care plan. Finally, lung transplantation remains an option for advanced, progressive ILD unresponsive to other treatments. The choice of therapy is often individualized based on disease severity, progression, and patient-specific factors.

Turning back time: Reversal of fibrosis as a critical target

Unfortunately, the currently available treatments typically only slow the inexorable progression of fibrosis in many ILDs and do not cure existing damage. Normally, myofibroblasts—a cell type that forms in response to tissue injury and aids in tissue repair—undergo controlled cell death and are removed. In progressive fibrosing ILDs like IPF, these cells become resistant to clearance, depositing scar tissue and sending pro-inflammatory signals to nearby cells in an uncontrolled manner. While the recently approved standard-of-care drugs nintedanib and pirfenidone have shown efficacy in stabilizing disease in patients with IPF, these treatments do not reverse existing fibrosis.  Thankfully, there have been recent advances including the development of phosphodiesterase 4B inhibitors, which have shown promise in stabilizing pulmonary function in early trials (one instance of which is in ongoing trials by Boehringer Ingelheim), but further research is needed to confirm their efficacy and safety. The Thannickal Lab at the Tulane University School of Medicine is investigating potential gene silencing treatments which could reverse the cellular changes leading to collagen deposition in fibrosis. Additionally, a recent spin-out of the University of Washington School of Medicine’s Institute for Protein Design is developing a miniprotein binder to inhibit αvβ6 integrin, a protein that promotes fibrosis, and is currently carrying out Phase II trials. But even with these potential advances on the horizon, it is clear that further research and innovation are crucial to discovering effective treatments that can halt – and ideally reverse – fibrosis progression.

Advances and challenges in ILD

Significant progress in diagnosis and treatment has improved patient outcomes, but much work remains. Parsing the complex, heterogeneous collection of diseases under the ILD umbrella requires extensive knowledge and ongoing, strategic collaborations among multidisciplinary experts. Advances in medical research and artificial intelligence, along with improved diagnostic criteria, may help reduce the burden of initial disease characterization. However, there are still no remedies for existing lung damage. Specialized centers and collaborative research networks are advancing care and fostering innovation, offering hope for new treatments that can significantly improve the quality of life for those affected by ILD and their families.

 ____________________________________________________

The Tulane Medicine team, who is also the Tulane Digest Team, is partnering at BIO 2024 this week. You can send a request through the BIO partnering system, or email us directly to arrange a time to connect.

____________________________________________________

Recent Podcast Episode Drops:

Whether for travel entertainment or a quick listen between meetings, check out 6 recently released bite-size episodes of BIO from the BAYOU. Check them out on the BftB Website, Apple Podcasts, Spotify, or anywhere you podcast.

____________________________________________________ 

Share the Science: Please forward this issue and encourage others to sign up for Tulane School of Medicine’s Digest Mailing List.

___________________________________________________ 

Curated Research and Research-Related News Summaries, Analyses, and Syntheses. Published on behalf of The Tulane University School of Medicine. Content is generated by reviewing scientific papers and preprints, reputable media articles, and scientific news outlets.  We aim to communicate the most current and relevant scientific, clinical, and public health information to the Tulane community – which, in keeping with Tulane’s motto, “Not for Oneself but for One’s Own”, is shared with the entire world.

Alexis L. Ducote, PhD: Editor-in-Chief

Special thanks to James Zanewicz, JD, LLM, RTTP and Elaine Hamm, PhD for copy-editing assistance.