Academic research – Page 122

May 20, 2026

Standardizing Cell Therapy Production with Technology Facelift

From a manufacturing standpoint, cell therapies are a disparate group of products, each requiring different starting materials and unique production processes. And, for an industry looking to standardize, this diversity is proving to be a challenge.

So says Marta Costa, PhD, a principal scientist at Portugal-based R&D non-profit, IBET, and co-author of a new study looking at efforts to make cell therapy production more time and cost efficient.

“Manufacturing cell therapies depends heavily on the cell type, therapeutic modality, and the clinical application, which makes production quite diverse. Different cell types have distinct requirements for cell sourcing, expansion, genetic engineering, and downstream processing,” she tells GEN.

Costa cites the differences between patient-specific autologous therapies—where cells are collected, modified, and reinfused—and allogeneic therapies—which are made from donor-derived or stem cell banks for multiple patients.

“Autologous manufacturing is individualized and tends to be decentralized, while allogeneic manufacturing explores scaled bioprocesses to produce larger cell batches in often centralized operations. Besides, even within the same therapeutic class, manufacturing can vary according to disease indication, donor material, genetic engineering strategy, and quality requirements,” she says.

Technology

Despite these challenges, industry’s ever-present desire for efficiency means standardization efforts continue. The current focus is on using closed, automated, and modular platforms to create reproducible workflows, Costa adds.

“Key enabling technologies of next-generation cell therapies will likely explore automated and closed platforms to reduce the risk of variability introduced by manual operations, reduce labor intensity, and, overall, improve consistency in operations that range from the initial cell isolation and selection of starting material up to fill-and-finish.

“In addition, tools like bioreactors, particularly when combined with process analytical technologies, provide tighter control over culture conditions and offer the opportunity to not only monitor but also adjust operations to ensure final cell quality,” she says.

Digital standardization

Digital technologies, such as electronic batch records, are also changing production, according to Costa, who says, “These strategies contribute not only to improve efficiency but also to enhance reproducibility, decrease COGs, and ensure compliance.”

In the future, artificial intelligence will also have a role to play, Costa says, as cell therapy firms will use the technology to make production more reproducible and data-driven.

“Although AI is unlikely to eliminate biological variability, its value probably lies in increasing process understanding and control. Examples of strategies already in place exploring AI are in predictive process control to optimize conditions before failures occur and in cell quality prediction, reducing reliance on end-point testing,” she said.

AI could also help manufacturers determine which quality attributes have the biggest impact on therapeutic efficacy, according to Costa.

“Identification of critical quality attributes is also another capability where AI could play a significant role, helping manufacturers understand which variables most strongly affect therapeutic performance.

“And, of course, automation is already viewed as a practical pathway toward standardization because it reduces operator-to-operator variation, contamination risk, and batch failures,” she says.

The post Standardizing Cell Therapy Production with Technology Facelift appeared first on GEN – Genetic Engineering and Biotechnology News.

May 20, 2026

Mutating Antibodies for Easier Drug-Conjugate Manufacturing

Scientists in the United States have developed a general-purpose antibody that they hope will help revolutionize antibody-drug conjugate (ADC) manufacturing. The team, from Johns Hopkins University, says they mutated the fragment crystallizable (FC) region, the part of an antibody that modulates immune response. The aim was to create new sites to attach molecules, including nanoparticle drugs or fluorescent markers for quality assurance.

According to Jamie Spangler, PhD, associate professor of biomedical engineering and chemical & biomolecular engineering, the new antibodies could—in the future—lead to more effective and easier-to-manufacture drug conjugates.

“The chemistry of antibody drug conjugates is so heterogeneous. It can be hard to characterize the drug-to-antibody ratio and to [do things like] maintain consistency in formulations.”

To get around this problem, Spangler’s team installed six mutations on the FC region of an antibody that can act as attachment sites for a variety of molecules. The team was able to attach a dye to quantify how many sites were available and discovered the best productivity was found when using up to four sites.

They emphasize that the sites can be used for many purposes.

“You can attach whatever you want,” Spangler explains. “You could use [them] to make an antibody-dye conjugate or even a drug conjugate.”

According to Spangler, the team has already shown that the mutations can be used to conjugate with nanoparticles. “We encapsulate the protein we want to deliver within the nanoparticle, and then we coat the surface with an antibody. The nanoparticle we’re carrying, in this case, contains some GFP [green fluorescent protein], which is a fluorescent readout, but we can attach that to an antibody.”

After the antibody binds to a cell expressing the target, it’s internalized, and the nanoparticle can release its cargo, she explains. This system can be used for any number of purposes.

“The sky’s the limit for how people want to use this in their own research and their own work,” she says. “It’s a fully tuneable and generalisable system, and we’d encourage people to think broadly and creatively about the different attachments they can use.”

The post Mutating Antibodies for Easier Drug-Conjugate Manufacturing appeared first on GEN – Genetic Engineering and Biotechnology News.

May 20, 2026

Mixed-Reality Fermentation Simulator Preps Workforce

Hands-on biomanufacturing training is expensive, regardless of whether that training occurs in manufacturing facilities where training may take production units offline, or in community colleges and universities where the availability of equipment and consumables may limit training time.

A mixed-reality fermentation training platform dubbed BioSuite Virtual solves much of that challenge.

Developed by Prism Immersive with funding from BioMADE and expertise from an industry consortium, BioSuite Virtual immerses learners in a world in which they interact with a virtual bioreactor in their physical space. Conversely, the perhaps more familiar augmented reality lets learners interact with physical objects with virtual overlays.

BioSuite Virtual consists of more than 40 different modules across 12 chapters, starting with a short introduction to the biomanufacturing space, followed by content-specific modules.

“It’s end-to-end fermentation training,” Jared DeCoste, PhD, CEO and co-founder of Prism Immersive, tells GEN. “Learners gain vital skills along the way as they assemble a bioreactor, sterilize it, inoculate it, add the media, set the controls, and perform a run. They monitor the run by taking samples and observing the fermentation conditions, making necessary adjustments throughout.” As a learner, “you can do things multiple times if you need to. You can start and stop. You can go at your own pace, all the way through the run.”

Shaped by fermentation SMEs

Training is based on best practices from industry subject matter experts—especially Amyris, which shared its processing best practices and expertise with Prism early on—and partners at Bioscience Core Skills Institute (BCSI), Northeastern University, and Harford Community College who shaped and piloted the software. Prism made these connections with the support of BioMADE’s member network.

This lets all users learn from what Dan Beaupré, COO and co-founder of Prism, calls “the best of the best” in precision fermentation. “BioSuite Virtual is informed by dozens of subject matter experts [from industry],” he stresses.

“BioSuite Virtual isn’t meant to completely supplant in-person training,” Beaupré adds. “It’s a precursor, where users can obtain literacy and develop operational familiarity with precision fermentation workflows before they touch real equipment.” Because they have this foundation, trainers can then focus on teaching more complex processes and scenarios.

Prism’s first clients, community colleges, began using the virtual training tool this spring, and “about a dozen others” from Massachusetts to Hawaii are licensing it for use in the next academic year. DeCoste reports interest from contract development and manufacturing organizations and biopharma companies, too. “One of the great things about software is that you can modify it for the exact procedures utilized within [a specific] environment.”

Going forward, Prism Immersive plans to create new modules in such areas as biosafety cabinet operations and aseptic training, “because that’s what industry is calling for,” Beaupré says.

“All sorts of things are possible in XR [mixed, augmented, or virtual reality], as long as they’re well-designed,” Beaupré emphasizes. “Everything we do is intentional,” and knowledge checks are built in to reinforce and validate learning. After successfully completing the course, learners have the option to be credentialed through BCSI.

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May 20, 2026

Anti-Inflammatory Drug Could Help Some People with Depression

Research led by the University of Bristol suggests treatment with an anti-inflammatory drug, already approved to treat arthritis, could help some people with depression.

The study, published in JAMA Psychiatry, was small but showed gradual improvement in the severity of depression and physical symptoms like fatigue, as well as a lowering of anxiety in those treated with tocilizumab versus placebo.

“Low-grade systemic inflammation is a putative causal factor in depression, present in approximately 30% of patients,” write co-lead author Golam Khandakar, MD, PhD, a professor and researcher at the University of Bristol, and colleagues.

“Individuals with difficult-to-treat depression have higher cytokine, e.g., interleukin 6 (IL-6) and C-reactive protein (CRP) levels, than treatment-responsive patients and controls.”

Tocilizumab is a humanized monoclonal antibody that blocks the IL‑6 receptor and is used as an immunosuppressive drug in several inflammatory and cytokine‑driven conditions. For example, it is approved by the FDA to treat rheumatoid arthritis and cytokine release syndrome in patients with severe COVID-19.

To test whether IL-6 inhibition could help people with depression, the authors carried out a small randomized controlled trial as a proof-of-concept study. Overall, 14 participants were given a tocilizumab infusion, and 16 participants were randomly assigned to receive a saline placebo infusion.

Adults were eligible to be in the study if they had moderate‑to‑severe, difficult‑to‑treat depression despite antidepressants, showed persistent low‑grade inflammation on repeat CRP tests, and had prominent physical depressive symptoms like fatigue.

After receiving a single infusion, the participants were followed up for four weeks with evaluations at one week, two weeks and four weeks. All were taking anti-depressants when enrolled and continued them during the trial.

The trial was not large enough or long enough to show a statistically significant improvement, but it did show a consistent pattern of greater, clinically sized improvement with tocilizumab by the end of the follow-up period, especially in patients with higher baseline CRP.

No real differences were seen at one or two weeks, but at four weeks people given tocilizumab showed bigger improvements in overall depression scores, fatigue, energy levels, anxiety and quality of life than those in the placebo group. Around 54% of participants in the tocilizumab went into remission at four weeks versus 31% of the placebo group.

“This work represents an important milestone in the development of new treatments for depression especially difficult-to-treat depression, which affects millions of people in the U.K. alone,” said Khandakar in a press statement.

“This is one of the first randomized controlled trials to test immunotherapy for depression, the first to test the IL-6 receptor as the treatment target, and the first to use a targeted approach to select patients most likely to benefit, and to show that it works.”

The researchers now want to carry out a larger randomized trial to assess if the effects they saw are significant in a bigger treatment population.

The post Anti-Inflammatory Drug Could Help Some People with Depression appeared first on Inside Precision Medicine.

May 20, 2026

Carolina Aguilar: Brain-Computer Interfaces that Heal Neural Circuits

Jonathan D. Grinstein, PhD, North American Editor of Inside Precision Medicine, hosts a new series called Behind the Breakthroughs that features the people shaping the future of medicine. With each episode, Jonathan gives listeners access to his guests’ motivational tales and visions for this emerging, game-changing field.

Brain-computer interfaces have captured global attention in recent years, but most public discussion has focused on assistive technologies—systems designed to help patients control computers, prosthetics, or digital devices through thought alone. Carolina Aguilar, co-founder and CEO of INBRAIN Neuroelectronics, believes the larger opportunity lies elsewhere: using advanced neural interfaces not just to decode the brain but to treat disease directly. Built around graphene-based technology, INBRAIN is developing implantable systems capable of reading and writing neural signals with far greater precision than traditional metal-based devices.

Before founding INBRAIN, Aguilar spent 13 years at Medtronic, including a decade leading the company’s global neuromodulation business. During that time, she saw both the extraordinary potential of brain stimulation therapies and the limitations of incremental innovation inside large medical technology companies. Her background in neuroscience research, including early work studying the relationship between pesticides and Parkinson’s disease, shaped a long-term interest in circuit modulation and neurotherapeutics. That experience eventually converged with the emergence of graphene as a promising material for next-generation neural interfaces.

In this conversation, Aguilar discusses why INBRAIN chose to focus on therapeutic BCI applications rather than assistive computing, how graphene may enable higher-resolution neural decoding and stimulation, and why Parkinson’s disease became the company’s first major target. She also outlines INBRAIN’s broader vision for personalized neurotechnology, AI-driven therapies, and future applications ranging from epilepsy and memory restoration to bioelectronic treatments for cardiometabolic disease.

This interview has been edited for length and clarity.

IPM: You spent more than a decade at Medtronic before founding INBRAIN. What made you realize that incremental innovation was no longer enough, and why did graphene feel like the right breakthrough technology at the right time?

Aguilar: INBRAIN is a graphene-based brain-computer interface (BCI) company developing the most intelligent and adaptive interface between the neural system and AI to solve health for billions.

I started my career in consumer goods, but then I spent 13 years at Medtronic, where, for ten of those 13 years, I was leading the brain stimulation, or neuromodulation, business globally. I was always extremely impressed by what the company vision was and the number of disease areas and patients that we could help. However, I saw that every year we were innovating, but it was a bit incremental versus breakthrough. It’s normal for big companies to prioritize preserving shareholder value and revenue opportunities.

Investing in breakthroughs is harder; they usually just acquire those breakthroughs and then integrate them. And, of course, they revitalized their innovation. So I thought at that point that I could be one of those breakthrough innovators that could take a little bit more risk but then bring much bigger value into the field.

When the right opportunity presented itself to us, after the European Union put €1 billion into bringing graphene to market and after having gone through different speeds as pieces, we realized that it was the time to build INBRAIN and make that breakthrough a step instead of the incremental innovation of the past.

It’s interesting because I actually studied neuroscience at Virginia Tech, and at Virginia Tech, I had to define my thesis to study for my master’s degree. I picked up a combination of pesticides in the study. The study focused on the effects of pesticides and their combinations on brain chemistry in Parkinson’s disease. Right. So it was already quite oriented toward what we are solving today. And I got a grant award for the best vision on circuit modulation. So it was not about targeting the brain. It was about the circuit that was actually managing some of these dynamics of Parkinson’s disease.

At that early stage, I was already very attracted to the problem we are solving today, even though I did not know I would have a company dedicated to that field and to this innovation. However, it was always driving me in that direction. Medtronic was the company that turned that ambition into a real product and broad platform, which I also helped launch globally. So I guess it was always there. It was the seed that had been growing over time.

IPM: Medtronic exposed you to commercial, upstream product development, and engineering challenges. What did you learn that prepared you to build INBRAIN, and how did graphene change your engineering perspective?

Aguilar: It also evolves over time. So we start with a problem, such as pesticides in the development of Parkinson’s. Then I think I stepped into Medtronic as a solution to the problem that existed at that time. I was like, great. Now we have a problem. We have a solution. Let’s fix Parkinson’s disease.

At Medtronic, I was exposed to new experiences even while working in a commercial role, as I became a global director. I was exposed to the upstream. At Medtronic, there is a downstream process from which all employees receive their compensation. Then there’s the upstream piece, which is the product development and the planning of the next platforms. I was not in charge of that, but I was exposed to the process, the thinking, what is coming next, how we can make it happen, and where the constraints are. And that intrigued me a lot.

I discovered that I had a little bit of an engineering part inside of me that I never exploited. When the right opportunity came, I received a call from an investor friend of mine, who sometimes asked me to do some small due diligence. And he said, “Hey, there are some guys who have some graphene technology here that you might understand better than me. Do you want to come to the pitch?” I said, “Perfect.”

Then I saw that some of these constraints that we were dealing with in Medtronic in terms of miniaturization, higher-resolution interfaces, charge injection limits, and many of these engineering problems, partially, we could also solve by going graphene and going a different kind of electronics and a different kind of platform. When these consolidated and we created INBRAIN, I had to put a huge amount of effort into understanding semiconductors, microelectronics, mechanical configurations, and data architectures. So it’s been a huge learning journey for me.

IPM: INBRAIN appears to be building a platform strategy across multiple applications and devices. What are the product verticals and why does graphene offer capabilities that traditional neural interfaces cannot?

Aguilar: So it’s effectively a platform with three product verticals. When Morgan Stanley released the BCI industry report, it stated that the market was a $400 billion opportunity. We already knew that with one device, you could not capture all that immense market. So we were already working on a stepwise approach to the biggest opportunity. And this is what we have today on the table in the sense that we have a first product. The first product I can show you is a cortical interface. Starting with about 100 contacts, we can grow to a thousand. But in this case, it was not necessary.

It’s made of graphene. So it’s not about the number of contacts but the quality of what these contacts can decode. What is the precision of anatomy and the resolution of disease-related biomarkers that we can decode at high resolution in a way that that resolution is superior to a standard medical technology?

In some cases, standard platinum and iridium are used; in some cases, iridium oxide. We decided to create this first product for use for less than 30 days once it’s approved. It’s not yet approved, but we are getting closer, and it is the one that we actually took first-in-human. The results of those three reports are being generated using this device to demonstrate both the safety of graphene and its decoding superiority compared to metal technology. And, of course, within that first-in-human study, we also decoded speech at the phoneme level.

It was about creating the first step toward making graphene and consolidating advanced materials in clinical practice. So from there, the second product is actually an implantable platform that uses some of that configuration. So we use a cortical and subcortical interface to actually decode a circuit.

In our case, the microcircuit that is involved in Parkinson’s disease. And that is the second one. And the third product is actually the same platform, where instead of these two cortical and subcortical interfaces, we put in the central nervous system. We are truly connected to a vagus nerve interface that decodes the fibers within the vagus nerve, which go into the different modulations of the different organs of the body.

We go from reading the brain to reading the body. This sequence of product verticals opens up the immense possibility of a $400 billion opportunity. But even more important is the number of patients we could actually touch and improve therapeutically with such a platform.

IPM: Many BCI companies focus on assistive applications like computer and prosthetic control. INBRAIN appears to be therapeutic. Why did you choose direct disease treatment, and what makes it harder?

Aguilar: People say “invasive” or “noninvasive.” I call them implantable and non-implantable. And within the implantable, there might be different levels of invasiveness, but we were looking at the problem to solve, and especially coming from the field we come from and having experience for ten years, the use cases we saw are assistive BCI, meaning I transfer thought to action in the computer as solving a very important problem, but actually in a small population because, at the end, paraplegia and ALS. They are very important disease areas, but compared to other areas, there are smaller populations.

There were many people and companies, great companies, already aiming to solve that. So Neuralink and Synchron and Paradromics were always positioned there. And we thought, well, we have a similar approach, but maybe with a material that is much better suited to actually read and write bidirectionally, therapeutically. In assistive BCI, you do a ton of decoding. So, you read it and then transfer it to the computer. On the therapeutic side, where we are doing it, you have to read, write, and do that computing already within the implanted system.

It’s a much more complex architecture and a harder problem to solve. Now the benefit is solving the disease for as long as the system is active. And Parkinson’s was only the beginning. We are currently examining the validation of this program. We’re looking at memory restoration. We are looking at a set of disease areas on the cardiometabolic side that I cannot disclose without an NDA that we are developing with Merck KGaA. Those deals were unexplored or suboptimally explored by some of the low-resolution companies in the field.

The post Carolina Aguilar: Brain-Computer Interfaces that Heal Neural Circuits appeared first on Inside Precision Medicine.

May 20, 2026

Systemic inflammation response index as an independent predictor of unfavorable prognosis and its application in risk stratification in patients with aneurysmal subarachnoid hemorrhage

BackgroundAneurysmal subarachnoid hemorrhage (aSAH) is a devastating cerebrovascular disease associated with high rates of mortality and long-term disability. Early risk stratification is essential to guide personalized management. Systemic inflammation plays a key role in secondary brain injury after aSAH. The systemic inflammation response index (SIRI), a novel inflammatory marker combining neutrophil, monocyte, and lymphocyte counts, has shown prognostic value in multiple disorders, but its long-term prognostic role in aSAH remains unclear.ObjectivesThis study aimed to investigate the association between admission SIRI and 12-month unfavorable functional outcomes (modified Rankin Scale [mRS] ≥ 3) in patients with aSAH, verify its independent prognostic value, and construct a clinically useful prediction nomogram.MethodsA retrospective cohort study was performed including 258 patients with aSAH admitted between January 2021 and December 2024. Patients were divided into a favorable prognosis group (mRS 0–2, n = 158) and an unfavorable prognosis group (mRS ≥ 3, n = 100). Baseline characteristics, imaging indices including modified Fisher scale, laboratory parameters, and treatment data were collected. Multivariate logistic regression with forced entry was used to identify independent prognostic factors. Restricted cubic spline (RCS) analysis was applied to explore the non-linear relationship between SIRI and prognosis. A prediction nomogram was constructed and validated using temporal validation (training cohort n = 170; validation cohort n = 88). Model performance was evaluated using discrimination, calibration, and decision curve analysis.ResultsSIRI was significantly higher in the unfavorable prognosis group (p < 0.001). Multivariate analysis confirmed that SIRI (OR = 1.20, 95% CI: 1.08–1.34, p = 0.001), age, hypertension, GCS score ≤ 8, modified Fisher scale, and treatment modality were independent prognostic factors. RCS analysis demonstrated a non-linear relationship (P for nonlinearity = 0.020), with a clear threshold at SIRI = 4.36; the risk of unfavorable outcomes rose steeply above this cutoff. The nomogram showed excellent discrimination (AUC = 0.881 in training; 0.919 in validation) and satisfactory calibration. Decision curve analysis confirmed favorable clinical utility.ConclusionAdmission SIRI is an independent predictor of 12-month unfavorable functional outcomes in patients with aSAH. A threshold value of 4.36 can effectively identify high-risk patients. The SIRI-integrated nomogram provides accurate and individualized prognosis prediction across both training and temporal validation cohorts. This validated tool provides robust evidence to support clinical risk stratification and personalized decision-making.

May 20, 2026

Machine learning-based morphological brain analysis in schizophrenia and unaffected siblings: a multisite study of potential risk markers

Background and hypothesisAssessing schizophrenia risk factors is crucial for developing early preventive interventions. We hypothesized that unaffected siblings, who share high genetic risk, exhibit neuroanatomical signatures similar to affected patients, potentially reflecting early pathogenic processes.Study designTo overcome single-center limitations, we analyzed 1,018 participants from five independent, public databases. Brain MRIs were standardized via voxel-based morphometry, and covariate-adjusted z-scores were calculated for regional volumes. An ensemble support vector machine (SVM) approach, incorporating multiple models to ensure robustness, was employed to extract a multidimensional brain signature, from which a schizophrenia-like score (SPS) was derived.ResultsThe ensemble SVM achieved high classification performance (AUC = 0.99861). Across all databases, patients exhibited consistent volume reductions in frontal, temporal, insular, and thalamic regions, alongside globus pallidus enlargement. Notably, unaffected siblings were 3.8 times more likely to show brain morphological similarities to patients than were healthy controls. Furthermore, we identified a novel imaging phenotype in siblings: increased ventral striatal volume, which positively correlated with the SPS. This feature, absent in established schizophrenia, suggests a potential compensatory mechanism or a transient developmental marker of risk.ConclusionApplying machine learning to large-scale, multi-site neuroimaging data effectively identifies structural endophenotypes. Our findings highlight unique structural characteristics, specifically the enlarged ventral striatum, as a critical biological metric for identifying high-risk individuals before clinical onset.

May 20, 2026

Perceived stress and mental health in perimenopausal women: a serial mediation study of psychological distress and social support

BackgroundThe perimenopausal phase is associated with a significantly higher prevalence of mental health disorders in women, with stress perception emerging as a pivotal risk factor. However, the psychological and social mechanisms through which stress perception influences women’s mental health during this period remain to be fully elucidated. This study aims to use a stress process model to examine how social support mediates the link between stress perception and psychological symptom severity during perimenopause.MethodsA cross-sectional survey design was used, and 549 Chinese perimenopausal women were surveyed through face-to-face questionnaires. The survey employed the Chinese Perceived Stress Scale, Kessler Psychological Distress Scale, Perceived Social Support Scale, and Psychological symptom severity (BSRS-5) to evaluate participants’ psychological symptom severity. The researchers used SPSS 26.0 for related analyses, PROCESS macro software for regression analyses, and applied the Bootstrap method to assess mediating effects.ResultsThe findings of the study indicate that perceived stress, psychological distress, and psychological symptom severity (BSRS-5) are significantly and positively correlated, and perceived social support is significantly and negatively correlated with these variables (P < 0.01). The study reveals that perceived stress significantly increases psychological symptom severity scores(BSRS-5) (effect size=0.493, 59.60%) after adjusting for confounding variables. Additionally, psychological distress and perceived social support independently mediate this relationship (effect sizes=0.204, 24.67% and 0.101, 12.21%, respectively). Additionally, perceived stress indirectly affects psychological symptom severity(BSRS-5) through the chain-mediated mediating pathway of “psychological distress → perceived social support” (effect size = 0.030, percentage = 3.62%).ConclusionStress can directly increase psychological symptom severity in perimenopausal women and indirect effects can be observed through mediating factors such as psychological distress, perceived social support, and the chain-mediated relationship between these two elements. Thus, reducing symptom severity is essential for improving mental health. The study indicates that enhancing the mental health of this group requires a multifaceted approach. This approach should focus on the alleviation of psychological distress and the promotion of social support systems. This will effectively disrupt the cycle of stress and psychological distress.

May 20, 2026

Sleep quality and its associated factors among women of reproductive age in Ethiopia: a systematic review and meta-analysis

BackgroundQuality sleep is vital for women’s health during reproductive years, affecting both physical and mental well-being. In Ethiopia, socio-economic and cultural factors worsen sleep issues, but data on this demographic are scarce. This systematic review and meta-analysis assesses the prevalence of poor sleep quality among Ethiopian women and identifies contributing factors, aiming to inform interventions and policies to improve sleep health in low-resource settings.MethodThis systematic review followed PRISMA guidelines and searched PubMed, Scopus, and Web of Science for observational studies. We included studies utilizing the Pittsburgh Sleep Quality Index (PSQI), as it is the most widely validated tool for assessing subjective sleep quality across diverse populations. Reviewers independently screened articles using Rayyan and assessed study quality with the Joanna Briggs Institute tools. Data were analyzed using Stata version 17. To account for potential clinical and methodological variability across studies, a random-effects model was employed to pool results, with heterogeneity assessed using statistics and the Cochrane’s Q test. Publication bias and sensitivity analyses were also performed.ResultNine studies involving 4,376 women of reproductive age (15–49 years) in Ethiopia were included. The pooled prevalence of poor sleep quality was 49.17% (95% CI: 35.29, 63.08). Significant predictors of poor sleep quality included intimate partner violence (OR: 3.24), depression (OR: 3.37), unplanned pregnancy (OR: 2.71), multigravidity (OR: 2.61), and substance use (OR: 2.24).ConclusionA systematic review indicates that nearly half of Ethiopian women of reproductive age experience poor sleep quality. Key factors include unplanned pregnancies, substance use history, intimate partner violence, previous depression, stress, being in the third trimester, and comorbidities; these need urgent attention and the implementation of screening and preventive measures. Future research should focus on effective interventions to improve sleep quality in these populations.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42023455867.