AI and Machine Learning in Peer Review: Improving Efficiency and Reducing Bias

by Turacoz | May 25, 2025 | Medical Writing

Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing various sectors, peer review in academic publishing is no exception. The integration of AI and ML into the peer review process promises to enhance efficiency, reduce bias, and ensure high-quality scholarly communication. This blog explores how AI and ML are transforming peer review, the potential benefits, and the challenges associated with their implementation.

Need for AI in Peer Review

The peer review process plays a key role in academic publication, to ensure the authenticity and quality of scholarly articles. However, this system is under significant strain due to the increasing volume of manuscript submissions. According to a study, manuscript submissions have been growing at an annual rate of 6.1% since 2013, leading to a substantial increase in the workload for peer reviewers. Traditional peer review is time-consuming, with estimates suggesting that over 15 million hours are spent annually on reviewing manuscripts often resubmitted to other journals after rejection [1].

AI and ML can alleviate some of these burdens by automating parts of the review process, thereby saving time and resources. These technologies can perform initial screenings, check for plagiarism, ensure adherence to formatting guidelines, and even assess the quality of a manuscript. Such automation can free up reviewers to focus on more complex and subjective aspects of the review process.

How AI and ML Enhance Peer Review

1. Automated Screening and Quality Checks

AI tools can automate the initial screening of manuscripts. For example, software like Statcheck and Penelope.ai can verify the consistency of statistical reporting and check whether a manuscript meets a journal’s structural requirements. These tools can quickly identify common issues such as plagiarism, incorrect formatting, and language errors, which might otherwise delay the review process.

2. Reviewer-Document Matching

Matching manuscripts with appropriate reviewers is another area where AI can make a significant impact. Traditional matching relies heavily on the expertise of journal editors, but AI can analyze the content of manuscripts and reviewer profiles to suggest the most suitable reviewers. This speeds up the process and ensures that the reviewer has the relevant expertise, potentially leading to more thorough and insightful reviews.

3. Predicting Review Outcomes

AI can also be trained to predict the likely outcome of a peer review based on the manuscript’s content. A study demonstrated that a neural network trained on a large dataset of manuscripts and their corresponding reviews could predict review scores with a high degree of accuracy [1]. While AI cannot replace human judgment, it can assist editors in making preliminary decisions, such as identifying manuscripts that are likely to be rejected due to poor quality.

Reducing Bias in Peer Review

Bias in peer review is a well-documented issue. Reviewers may be influenced by factors such as the author’s institution, gender, or nationality, leading to unfair evaluations. AI and ML have the potential to mitigate these biases by providing objective assessments based on the content of the manuscript rather than the identity of the authors.

• Uncovering Hidden Biases

AI can be used to analyze patterns in review data to uncover biases. For instance, an AI tool trained on a large dataset of peer reviews might reveal that certain types of papers or authors are consistently rated lower than others, regardless of the content. This information can help journals to develop strategies to address these biases and ensure a fairer review process.

• Ethical Considerations

Despite the potential benefits, the use of AI in peer review raises ethical concerns. One major issue is the risk of perpetuating existing biases if the AI systems are trained on biased data. For example, if past reviews have favored certain demographics or institutions, the AI might learn to replicate these biases. Therefore, it is crucial to ensure that AI systems are trained on diverse and representative datasets.

Another concern is the opacity of AI decision-making. Authors and reviewers may be skeptical of AI-generated recommendations if they do not understand how these decisions are made. Ensuring transparency in AI algorithms and providing clear explanations of AI decisions can help build trust among stakeholders.

Case Studies and Current Implementations

Several initiatives are already leveraging AI to support peer review. For instance, the National Natural Science Foundation of China uses AI to assist in the grant review process, aiming to reduce bias and the workload on reviewers. Similarly, the Canadian Institutes of Health Research have implemented an online system to manage grant applications, which has been praised for its ability to reduce reviewer fatigue and improve transparency.

Another notable example is the use of AI in MOOCs (Massive Open Online Courses) to assess student essays. Automated Essay Scoring (AES) systems, used by platforms like EdX, MIT, and Harvard, have demonstrated the potential of AI to handle large volumes of written work, providing timely feedback and maintaining consistent evaluation standards.

Future Directions

The future of AI in peer review holds many possibilities. Ongoing research aims to enhance the capabilities of AI systems to handle more complex aspects of the review process, such as assessing the novelty and significance of research. Additionally, integrating AI with other technologies, such as blockchain, could further enhance transparency and accountability in peer review.

1. Enhancing AI Capabilities

Future AI tools could be developed to provide more sophisticated analysis of manuscripts. For example, AI could be trained to evaluate the logical coherence of arguments, the robustness of methodologies, and the relevance of cited literature. This would require advances in natural language processing (NLP) and domain-specific training.

2. Blockchain Integration

Integrating blockchain technology with AI could address some of the transparency issues associated with AI in peer review. Blockchain can provide a tamper-proof record of the review process, ensuring that all decisions and changes are documented and traceable. This could enhance the credibility and accountability of the peer review process.

Conclusion

AI and ML offer promising solutions to many of the challenges faced by the traditional peer review system. By automating routine tasks, improving the matching of reviewers and manuscripts, and providing objective assessments, AI can enhance the efficiency and fairness of peer review. However, it is essential to address the ethical concerns and ensure transparency in AI decision-making. As these technologies continue to evolve, they hold the potential to transform peer review, making it more efficient, equitable, and reliable.

The integration of AI and ML into peer review is not just a technological upgrade but a fundamental shift in how we approach scholarly communication. By harnessing the power of AI, we can build a more robust and inclusive peer review system that upholds the highest standards of academic integrity.

References

1. Kousha K, Thelwall M. Artificial intelligence to support publishing and peer review: A summary and review. Learned Publishing. 2024 Jan;37(1):4-12.
2. Checco A, Bracciale L, Loreti P, Pinfield S, Bianchi G. AI-assisted peer review. Humanities and Social Sciences Communications. 2021 Jan 25;8(1):1-1.

How AI is redefining content creation in pharma — And why humans are still the drivers of trust

 **How AI is redefining content creation in pharma — And why humans are still the drivers of trust*

by Turacoz (https://turacoz.com/author/turcoz/) | May 20, 2025 | Medical Writing 

In an era where speed, efficiency, and personalization have become imperatives, Artificial Intelligence (AI) — particularly machine learning, AI algorithms, and generative AI — is revolutionizing how the pharmaceutical industry approaches content creation. From automating reference linking to generating first drafts, AI is making content smarter, faster, and more scalable.

Yet, amidst this digital acceleration, one thing remains clear that human expertise is still the foundation of trust in healthcare communication.

At recent industry events and conferences, thought leaders echoed a common sentiment: AI is a catalyst, not a replacement. The most impactful pharma content today is born from a powerful synergy between AI and human intelligence, particularly when applied across disciplines such as data analysis, pharmacovigilance, clinical trials, and drug development.

**The power of AI in pharma content creation**

AI has significantly shortened the timeline of content development. By automating routine tasks like data architecture, extraction, summarization, and even modular content creation, AI enables teams to focus on higher-value activities. Some of the key advantages include:

* **Speed and efficiency**: Drafting scientific summaries, creating modular content blocks, and auto-tagging assets for reuse — AI can perform these tasks in minutes, which previously took days.

* **Compliance and consistency**: AI can cross-reference regulatory guidelines and validate claims faster, ensuring fewer errors and a higher level of consistency across materials.

* **Personalization at scale**: Machine learning and AI algorithms help in tailoring content to specific audiences, ensuring that messaging is relevant, targeted, and timely – particularly in fields like personalized medicine and patient care.

The impact is undeniable. Pharma companies are no longer just creating more content — they are creating better content, delivered at the right time, to the right audience.

**Why humans remain at the heart of trusted communications**

Yet, even as AI transforms the operational side of content creation, human oversight remains indispensable for several reasons:

1. **Contextual accuracy and nuance**

Medical communication is not just about relaying information — it’s about conveying it with precision, empathy, and context. AI can process data, but only humans can interpret complex medical nuances, drug discovery insights, and cultural considerations that shape the right narrative.

1. **Ethical and regulatory oversight**

In the field of regulatory pharmalike pharmacovigilance and clinical trials, accuracy and ethics are non-negotiable. While AI can check references, it cannot assure about the ethical gray areas – a responsibility that remains with human experts.

1. **Building emotional connection**

Trust in healthcare communications is deeply emotional. Physicians, patients, and stakeholders seek authenticity and human connection – something machines like large language models cannot replicate. Skilled writers infuse compassion, clarity, and credibility into every piece of content, building the trust that AI alone cannot establish.

1. **Innovation and strategic thinking**

AI can optimize existing processes but cannot create disruptive strategies. Human creativity is still essential in commercial areas like customer engagement, content marketing, and long-term drug development strategies.

**The future is Human + Machine, Not Human vs Machine**

The future of pharma content creation lies in **collaboration, not competition**. AI — whether used in pharma AI tools, generative AI, or data analysis pipelines — should be seen as a powerful tool that augments human potential. When medical writers, regulatory experts, and creative strategists partner with AI, the result is content that is faster, smarter, and — most importantly — trusted.

At Turacoz, we believe that technology is only as powerful as the people who wield it. By combining the scalability of AI with the critical thinking, empathy, and expertise of humans, we help our clients craft communications that build lasting trust with healthcare professionals and patients alike.

**Final thoughts**

AI is redefining the way content is created in pharma, making processes smarter, faster, and more scalable — especially with advancements in AI algorithms, data architecture, and personalized medicine. But even the most sophisticated AI cannot replace the human touch that drives trust, credibility, and connection in healthcare communications.

As we embrace this exciting new era, the winning formula is clear: leverage the best of AI innovation, anchored by the irreplaceable value of human expertise.

*Ready to elevate your content strategy with the perfect blend of human insight and AI innovation? Connect with Turacoz today.*

World Thalassemia Day 2025: Giving a Voice to the Global Patient Community

World Thalassemia Day 2025: Giving a Voice to the Global Patient Community

by Turacoz | May 15, 2025 | Medical Devices, Medical Writing

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Every 8 May, World Thalassemia Day shines an international spotlight on the millions of people living with this inherited genetic disorder. The 2025 theme – “Together for Thalassaemia: Uniting Communities, Prioritising Patients” – captures the day’s core mission: to centre the patient, safeguard their rights, and ensure they are heard in every conversation about diagnosis, care, and cure.

Why patient voices matter

Thalassemia is more than severe anaemia or the frequent blood transfusions keep patient alive. It also means coping with fatigue, recurrent infections, painful splenomegaly, and the anxiety of waiting for a suitable bone marrow transplant. When patients share these everyday realities, they transform abstract epidemiology into human stories that resonate with policy‑makers, clinicians, and the public. Listening to patient experiences helps researchers design therapies that protect quality of life, not just haemoglobin levels, and reminds health systems that compassionate, patient‑centred care is a clinical imperative, not a luxury.

Awareness breeds early detection – and equity

World Thalassemia Day is the year’s biggest megaphone for public awareness. Broad campaigns that explain the difference between alpha and beta thalassemia, the role of genetic mutations, and the importance of early genetic counselling empower families to seek screening before the birth of an affected child. Awareness also normalises lifelong treatment – from iron‑chelation to emerging gene therapies – helping communities overcome stigma and misinformation. Crucially, it spotlights the wide gap in access to care between well‑resourced urban centres and low‑income regions where health inequalities still dictate life expectancy.

Patient advocacy: From individual struggle to collective power

Grass‑roots organisations turn individual stories into collective action. Their advocacy has expanded newborn screening programmes, secured government subsidies for transfusion supplies, and pressured insurers to cover expensive iron‑chelators. By partnering with scientific bodies, advocates elevate patient priorities on the global research agenda – accelerating healthcare innovation such as CRISPR‑based gene editing. This year’s theme urges deeper community engagement so local groups in Africa, South‑East Asia, and the Middle East can exchange strategies and unite around shared goals.

Public health policies that put patients first

No amount of patient courage can replace political will. World Thalassemia Day provides a rallying point for drafting evidence‑based public health and healthcare policies that guarantee timely transfusions, safe blood donation networks, and affordable chelation therapy. Advocates are calling for national guidelines that enshrine healthcare equality, fund specialised thalassemia centres, and subsidise cutting‑edge cures so that ability to pay never determines access to quality healthcare. Governments are also urged to adopt preventive measures—premarital carrier testing, public education on consanguinity risks, and school‑based disease prevention programmes—to curb the financial and emotional burden on future generations.

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• Donate blood – A single unit sustains a child with thalassemia for weeks.
• Champion prevention – Encourage friends to seek carrier testing and pre‑marital genetic counselling.
• Amplify stories – Share patient videos or blog posts on social media to shift the narrative from statistics to lived reality.
• Support research funds – Philanthropy accelerates clinical trials for curative therapies and less invasive treatments.
• Engage politicians – Write to representatives about the need for robust, patient‑friendly thalassemia legislation.

Looking ahead

World Thalassemia Day is more than a date on the calendar; it is a movement that refuses to let patients be passive recipients of care. By elevating their voices, the global community can drive healthcare access, reduce the financial burden of lifelong therapy, and ultimately fulfil the promise that no child will be barred from a healthy future because of an inherited blood disorder.

On this 8 May, Turacoz calls for the community support, systemic change, and truly person‑centred care reverberates far beyond a single day—until every patient, everywhere, is not just surviving, but thriving.

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