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Catching Up with Consulting — DIA 2024 Insights

This article is based on opinions and perceptions from the DIA 2024 Global Annual Meeting, in San Diego, June 2024. Many thanks to our contributors: April Purcell (Specialist) and Michelle Peter (Senior Specialist). The team sat down with Gail Winslow, Head of Marketing, after the conference to share their experiences.  

From start to finish, several key themes emerged. Artificial Intelligence in clinical trials dominated the agenda, mirroring its prominence in many industry events. International collaboration was also a major focus, highlighted by Japan’s PMDA taking a strong stance. Real-world data and real-world evidence were consistent undercurrents, alongside discussions on regulatory guidance and the urgent need to accelerate changes in clinical trials to bring new innovations to market faster and meet patient needs. 

Q: What were the most valuable insights or lessons you learned at the conference? 



Q: Was there a particular session or speaker that stood out to you? Why? 



Q: Were there any surprising or unexpected topics covered that you found interesting? Or was there anything you thought would be covered and wasn’t? 



Q: From what you learned, what is the best advice you would give to your clients having gone to this year’s DIA?  


Three essential pieces of advice include: 


Want to learn more about our DIA perspectives? Contact us today.  

Generative AI-Driven Clinical Trials: Are We There Yet?

This article is based on the session titled, “Generative AI-Driven Clinical Trials: Myth or Reality,” at the DIA 2024 Global Annual Meeting, in San Diego, June 2024. Many thanks to the presenters: Sharmin Nasrullah (Salesforce), Lichen Shen (Medidata), Aman Thukral (Abbvie), Lindsay Hughes (IQVIA), Jonathan Shough (Parexel), and Chunky Satija (Everest Group) for their valuable insights. This translation is the author’s rendering of their points and should not be taken as exact quotations. 

As we integrate artificial intelligence (AI) into clinical trials, it is crucial to establish guiding principles to prevent harm. Often, there is a temptation to prioritize speed over sustainability. Meanwhile, reproducibility and auditability are essential regulatory expectations for our industry.  

AI solutions must track information sources, and clinical trial processes should enable teams to build value from the vast data generated. Scaling efforts can be achieved through: 

  1. Transcription: Converting languages, text to code, or explanations. 
  2. Automation: Reviewing data, financial information, and creating forms. 
  3. Generation: Producing visualizations, synthetic data, or compound structures. 

Embracing AI Innovations 

Currently, many users rely on click-based user interfaces (UI), but the future lies in conversational UIs (i.e., ChatGPT, chatbots, Alexa), and our approach must evolve to leverage AI advancements.  

Clinical trials begin and end with data and documentation. Moving from hard-coded logic to large language model (LLM)-based workflows will revolutionize data integration, connecting sponsors, Contract Research Organizations (CROs), sites, and patients.  

Simultaneously, we can apply personalization to patient engagement and glean insights into patients’ previous healthcare interactions, use systems and sites to foster better patient engagement, and use the data collection for real world data. 

AI’s Role in Clinical Trials 

AI’s potential in clinical trials is vast. Generative AI can simplify communication and translate complex data into layperson language, so why do we continue to burden the patient with complex data and scientific jargon in the clinical trial process? We can’t throw a lot of data into a system, retrieve the data, and think patients will understand the complexities of the research. But we can implement generative AI to simplify communication to provide better translation to patients in a way they can understand and comprehend. Using tools like ChatGPT to bring information down to the layperson language enables better interaction and a better overall experience for the patient, while still showcasing to the clinical trial sponsor areas that need more simplification.  

Measuring AI Effectiveness 

Key performance indicators (KPIs) for AI in clinical trials include patient recruitment, site quality, site selection, and predicting protocol deviations. Implementing generative AI in literature reviews is one example of how we are integrating AI into our business practices. We need to do a better job of understanding and owning data quality across sponsor organizations. Is there a data governance plan? Is the data consistent between users who input and those who read outputs? These are all human-led ways we can make AI work.  

At Parexel, compliance with data quality is an annual performance review metric, measuring on-the-job action instead of training completion. Not all data is worthy of being input, so it’s critical to consider how you will use the data, how you will measure the data, and what privacy standards will be upheld. These questions require the strategy of humans to dissect and determine how we bring AI into our clinical trials.  

Challenges and Considerations 

Adopting generative AI at scale requires a mindful approach. Data quality and bias must be addressed, and the regulatory framework requires alignment. Data governance and inherent biases in AI, particularly towards a white male perspective, must be addressed. Training AI models and scrutinizing who creates these platforms are essential steps in ensuring ethical and inclusive AI integration in clinical trials.  

Clinical decision support, a system that provides information to clinicians, staff, and patients to help inform decisions about a patient’s care, must keep patients informed and involved in reviewing results and data. However, much of our data operates in silos, and integrating AI into workflows requires new skills and training, such as writing effective prompts. 

Audit trails and sharing best practices across the industry are also helpful in propelling mindful adoption. 

AI Obstacles and Watch Outs 

We are trying to be mindful of the lifecycle of adoption (think Gartner’s Hype Cycle).1 We know the stories in the news about the chatbots hallucinating.2 Issues around data quality and bias need to be taken into consideration and we need to establish audit trails and policy, and best practices need to be widely shared. Our historical interaction with technology is built on learning (new) skills, so we need to introduce this new training into our workflow, and we must learn how to write prompts to assist with our AI efforts.  

AI should augment, not replace, the clinician or clinical trial staff. We need to use AI as a tool for efficient patient communication. There’s inherent distrust of technology; for example, many people want to know from whom they are getting their information. Until we can trust the ‘realness’ of AI, we will not arrive at the place of widespread adoption in our industry.  

Machines are not inherently empathetic, so we must remember this vital ingredient in clinical trials – empathy. Remember, we are building technology solutions, and in the context of communicating complex messages, we cannot depend on AI to be the only end game.  

To navigate the complexities of AI adoption in your clinical trial, contact us. We’re ready to continue the conversation when you are. 


  1. Gartner. Gartner Hype Cycle.   
  2. The New York Times. Chatbots May ‘Hallucinate’ More often Than Many Realize.  

Clinical Trials in 2024 — Are We Making the Grade?

This article is based on the session titled, “The State of Clinical Trials in 2024: Are We Making the Grade?” at the DIA 2024 Global Annual Meeting, in San Diego, June 2024. Many thanks to the presenters: Summer Starling (CTTI), Jennifer Miller (Yale School of Medicine), and Linda Sullivan (Tufts Center for the Study of Drug Development) for their valuable insights. This translation is the author’s rendering of their points and should not be taken as exact quotations. 

In 2024, the clinical trials landscape is undergoing significant transformation. To gauge our progress and effectiveness, we must scrutinize the metrics and measurements driving clinical trial innovation and performance and get a handle on the enormous amount of data being generated. When the audience was polled, diversity, cost, and efficiency top the list of what comes to mind when thinking about measuring progress and improvements in clinical trials. While understanding impact and sharing meaningful results topped the audience list for what is the biggest change to implement for pursuing metrics and measurement in clinical trials. 

Linda Sullivan, from the Tufts Center for the Study of Drug Development, emphasized clinical trials are generating unprecedented amounts of data. This deluge raises critical questions about which data to prioritize and how to derive meaningful insights.  

One of Halloran’s key consulting services is tied to proactive planning to prepare your organization for evolving regulatory requirements impacting data integrity by implementing scalable data oversight processes, procedures, and governance to minimize risks. Our training programs aim to ensure your teams are equipped with the latest industry knowledge to strengthen your organization’s ability to handle the data deluge referenced in this session.  

Clinical Trials Transformation Initiative (CTTI) 

CTTI provides a strategic vision for transforming the clinical trials landscape by 2030. Their vision offers a comprehensive framework to measure and guide global clinical trial progress. CTTI has identified eight pillars essential for understanding and advancing clinical trial performance. These pillars serve as the north star, with each domain containing three specific metrics, culminating in 57 metrics to measure success across 19 domains.  

Pillars include patient-centered methodologies, improving access, full integration into health processes, designed with a quality approach, leveraging all available data, and improving population health.  

Innovative trial designs, such as pragmatic trials, simulations, and adaptive designs, are crucial for balancing innovation with practical applicability. Access to high-priority metrics necessitates exploring data collaborations, and socializing and publishing findings for public input is vital for refining and validating clinical trial approaches. This inclusive strategy seeks opinions and reactions to ensure comprehensive understanding and acceptance of clinical trial transformations. 

Linda Sullivan reminded the audience that the focus shifts to the messages conveyed by an organization’s metrics. Metrics should establish priorities, influence behaviors, and clarify what actions are rewarded or overlooked. This ties into the broader question of whether we are effectively measuring the right things and defining success appropriately. The metrics must help answer key questions, define acceptable standards, and motivate performance through effective communication. 

Organizations often focus on tracking issues rather than celebrating successes. Improving metrics involves not just highlighting what is going well but also showcasing where there are improvements to be made. This dual approach—akin to a good pharmaceutical scorecard—can spotlight positive frameworks and encourage transparency and accountability. The Good Pharma Scorecard, for instance, grades pharmaceutical companies on their performance and transparency, providing a model for clinical trial metrics.1 

Setting achievable performance targets and celebrating milestones is essential. Diversity in clinical trials remains a challenge, and realistic goals are crucial for making meaningful industry-wide progress. By refining our metrics, fostering innovation, and maintaining clear communication, we can ensure that clinical trials continue to evolve and improve, ultimately benefiting patients and advancing clinical research. 

Take a Stand 

What are you doing to advance clinical trials this year and beyond? Consider attending Halloran’s Clinical Operations Retreat for Executives (CORE) conference, October 16-18, 2024. CORE is an event designed for like-minded clinical operations executives and senior leaders in life science to talk through the most pressing issues around product development and building companies in this industry. Let’s continue the conversation and keep innovation at the forefront. To learn more, register here. 


  1. Bioethics International. Good Pharma Scorecard.  

The Upside of Artificial Intelligence on Medical Writing

This article is based on the session titled, “Shifting Medical Writing Value Propositions with the Use of Technology,” at the DIA 2024 Global Annual Meeting, in San Diego, June 2024. Many thanks to the presenters: Robin Whitsell (Whitsell Innovations), Joanne Hilton (GlaxoSmithKline), and Kayla Williams (Takeda) for their valuable insights. This translation is the author’s rendering of their points and should not be taken as exact quotations. 

The Evolution of Google Search: From SEO to AI Summarization 

Google, along with other well-known search engines, has long been a cornerstone of the way we access information. Historically, the internet relies heavily on search engine optimization (SEO) to provide website recommendations for search terms. Today, a new way of digesting key points in content through search engines is being ushered in with artificial intelligence (AI) driven summaries, which generate concise overviews of topics, presenting curated options directly to users. This shift signifies a profound change in how we interact with information online, raising both promises and concerns.  

Tools, like AI summarization technology, offer numerous benefits. They can streamline information retrieval, saving users time and effort by providing immediate answers to queries. For medical writers and life science companies, there is both optimism and caution tied to efficiencies being built and costs being reduced when using AI as part of their process. However, technology, regardless of its popularity and use, brings inherent limitations and biases that must be acknowledged and addressed. 

Potential Biases in AI in Medical Writing 

AI systems are only as good as the data in which they are trained. If the training data is biased, the AI’s output will also reflect those biases. For instance, if AI primarily processes information from sources dominated by a particular demographic, it may inadvertently perpetuate those biases. In the dynamic landscape of clinical research, ensuring diversity in clinical trials has emerged as a critical factor for the success of the healthcare ecosystem, and this kind of automated solution can be problematic.  

To mitigate these biases, it is crucial to approach technology and its use with caution. Overreliance on a solution just because it’s available, may provide cost savings, or because it’s a new wave, may result in failure to have your Investigational New Drug (IND) application accepted.  

Medical Writers Carry Essential Skills for the Future 

The rise of AI has sparked fears of job displacement, particularly in fields like medical writing where AI can handle tactical tasks. However, strategy remains a big part of the medical writing process. The medical writer serves as documentation architect, decision catalyst, initial draft writer, and curator of comments. To stay relevant, medical writing professionals must optimize their skill sets by focusing on areas that AI cannot easily replicate. 

During the presentation, it was boldly shared, “AI will not replace humans, but humans with AI will replace humans without AI.”   

Key skills for medical writers remain indispensable, including: 

Most medical writers possess a deep understanding of disease states or modalities, as this specialized knowledge will be increasingly valuable. While AI can assist with generating content, the strategic and creative aspects of writing still rely on human expertise. 

So, while technology powered advancements such as AI summarization represent a significant evolution in how we access and interact with information, the application of AI to the medical writing process continues to pose challenges which require careful human-intervention. By understanding and addressing the limitations and biases of AI, and by optimizing our skills and organizational strategies, we can harness the full potential of this technology to drive innovation and improve outcomes. 

Halloran’s Medical Writing Services  

Our medical writing services offer the proficiency and expertise to support our clients at every stage of development in crafting documents for regulatory submissions, investigators, and beyond. We tap into a wealth of regulatory, clinical development, and quality and compliance knowledge shared by Halloran consultants across all our services to meet your unique requirements.  

Whether you require all Module 2 written and tabulated summaries, the protocol, and the investigator’s brochure for your new Investigational New Drug submission, or if you have internal subject matter experts covering certain sections but need additional support in a critical area, we are poised to help your medical writing needs. Contact us. 

RWD and RWE for Regulatory and Health Technology Assessments

This article is based on the session “Real-World Evidence (RWE) for Regulatory and Health Technology Assessment Decision Making: Where Are We?” at the DIA 2024 Global Annual Meeting, in San Diego, June 2024. Many thanks to the presenters, Solange Corriol-Rohou and David Ross, both from AstraZeneca, for their valuable insights. This translation is the author’s rendering of their points and should not be taken as exact quotations.  

In recent years, the use of real-world data (RWD) and real-world evidence (RWE) has evolved significantly in the life science industry. Traditionally utilized for post-licensing for safety monitoring, RWD and RWE are now increasingly employed in pre-production stages and clinical trials. This shift raises numerous questions about the optimal use of such data during product development, including integrating patient experience data and patient-reported outcomes.  

Patient involvement is crucial, yet the primary methods of data collection—registries and digital health tools—pose challenges in terms of data acceptability by regulators. In December 2023, the U.S. Food and Drug Administration (FDA) published, “Realizing the Promise of Real-World Evidence.”1 To navigate these challenges, continuous communication with regulatory bodies is essential to gain their support for using RWD and RWE in clinical trials. 

We need to continue to implement RWD and RWE into clinical trials to understand disease and natural history, ascertain treatment patterns, optimize patient management, and expose the impacts to public health. RWD and RWE provide valuable insights into the patient perspective which otherwise may go unreported. However, this is not just a U.S.-centric challenge and opportunity.  

International Involvement 

European trade associations have formed specific groups dedicated to focusing on RWD, aiming to identify and establish standards. Within pharmaceutical and biotech companies, it is imperative to engage the right experts across different functions when considering RWD and RWE. This cross-functional collaboration ensures comprehensive evaluation and utilization of the data.  

Various international regulatory agencies have released independent guidance on the use of RWD and RWE in clinical trials, with the International Coalition of Medicines Regulatory Authorities (ICMRA) leading efforts to harmonize global standards. Lessons learned from the COVID-19 pandemic underscored the importance of sharing information and critical knowledge, which facilitated the rapid development and global distribution of vaccines. 

Global private-public partnerships are becoming increasingly common, with regulatory bodies collaborating to create shared learning opportunities. These partnerships encourage the dissemination of findings, provided there is an open dialogue with sponsor companies. 

Members of theInternational Coalition of Medicines Regulatory Authorities (ICMRA), a global conference of government health bureaucrats, include:


The Medicines and Healthcare Products Regulatory Agency is an executive agency of the Department of Health and Social Care in the United Kingdom which is responsible for ensuring that medicines and medical devices work and are acceptably safe. 

Health Canada 

Health Canada is the department of the Government of Canada responsible for national health policy.  


The primary regulatory bodies in the European Union (EU) are the European Parliament, the Council of the European Union, and the European Commission. 


The Swiss Agency for Therapeutic Products is the Swiss surveillance authority for medicines and medical devices. 

PMDA Japan 

Japanese regulatory agency, working together with Ministry of Health, Labour and Welfare.  

NMPA China 

The National Medical Products Administration is a national bureau responsible for drug supervision under the State Council of China and is managed by the State Administration for Market Regulation. 

TFDA Taiwan 

The Republic of China Food and Drug Administration is a Republic of China government agency, which is responsible for the safety and quality of food, drug, medical service and cosmetics. It is part of the Ministry of Health and Welfare. FDA is a regulatory member of ICH association. 


The United States Food and Drug Administration is a federal agency of the Department of Health and Human Services. 

Operational Considerations 

On the operational side, the landscape of RWD and RWE is vast and varied. It includes primary, secondary, and hybrid primary-secondary data sources such as filtered and unfiltered claims data, pharmacy data, pathology studies, electronic medical records (EMRs), and hospital and insurance claims.  

This plethora of information presents several challenges, including: 

Additional insights: Understanding the New FDA Guidance for Drug and Biological Product Submissions Containing Real-World Data to Successfully Navigate Regulatory Decisions 

To effectively manage these issues, the integration of metadata, semantic coding, and multiple data sources is essential. This approach ensures the application of FAIR (Findable, Accessible, Interoperable, and Reusable) principles. However, accessibility and reusability of data remain significant challenges. Leveraging artificial intelligence (AI) to process and analyze RWD and RWE can be critical in overcoming these hurdles, enhancing the efficiency and effectiveness of RWD and RWE utilization in regulatory and health technology assessment decision-making. 

Overall, the evolving landscape of RWD and RWE utilization highlights the need for continued innovation and collaboration among regulators, industry stakeholders, and researchers. By addressing the challenges and embracing new technologies, the potential of RWD to improve regulatory outcomes can be fully realized. 

Additional insights: Bringing In-vitro Diagnostics to Market With Real World Evidence  

How Halloran Can Help 

With the surge in technology adoption, clinical trial sponsors invest in diverse systems and services across all development phases, leading to a complex data ecosystem and massive data generation and transfer. Regulatory bodies, globally, are increasingly focused on data integrity and sponsor oversight. Our consultants excel in data integrity across domains, crafting strategies to ensure consistent integrity and inspection readiness. To learn more about how we can help, contact us.  


  1. U.S. FDA. Catching Up with Califf. Realizing the Promise of Real-World Evidence. Current as of December 21, 2023.  

Building Your Leadership Superpowers 

This article is based on the session titled, “Elevate Leadership: Harnessing the Five Superpowers,” at the DIA 2024 Global Annual Meeting, in San Diego, June 2024. Many thanks to the presenter: Vidya Narayanaswamy (IPM), for her valuable insights. This translation is the author’s rendering of their points and should not be taken as exact quotations. 

Lead with Compassion – the Key to Empowered Teams 

In every moment, leaders are faced with decisions which shape the future of their teams and organizations. The choices they make influence and impact the people they lead and the outcomes. To navigate these decisions effectively, leaders need more than just strategic acumen – they need compassion, authenticity, and resilience. 

These qualities foster trust, loyalty, and engagement, creating a thriving work environment. When it comes to leading clinical trials, leaders must also keep a compassionate patient perspective at the center of their work. 

Earlier this year, Halloran hosted a webinar titled, “Key Strategies for Development Stage Biotechs: Developing an Organization and the Talent Within.” To watch this webinar on-demand, click here. 

Empathize in Action 

Compassion in leadership goes beyond empathy; it is empathy in action. It’s about being there for your team, understanding their needs, and taking steps to support them. When leaders practice compassion with their team members, it leads to empowerment, reduces stress, increases happiness, and fosters loyalty and trust. This, in turn, results in better team engagement and performance, and less burnout. 

Incorporating daily doses of compassion can be transformative. Practice gratitude and recognize those who go above and beyond, sharing their achievements broadly. This not only amplifies their voices but also sets a positive example for others. 

Actively Listen 

Active listening is a cornerstone of compassionate leadership. Despite its importance, the rate of active listening is declining. Leaders must make a conscious effort to listen to their team members, ask open-ended questions, and offer support. Simple questions like “What can I do to make your day better?” or “What can I take off your plate?” show that you care. Sharing your own stories can also foster communication and help you see situations from your team’s perspective. 

Act with Integrity and Authenticity  

In an uncertain world, authenticity is more important than ever. Authentic leaders know themselves, their strengths, and weaknesses, and understand their triggers. They embrace vulnerability and lead with purpose. 

Authentic leadership also involves continuous self-discovery and growth. Spend at least an hour each week understanding yourself better. Develop a core group of allies with whom you can speak freely. Create a value system, take consistent actions, and seek feedback regularly. Embrace continuous improvement and stay up to date with new knowledge and skills. 

Communicate with Transparency 

Authentic leaders communicate openly and transparently, especially during difficult times. For instance, in the event of layoffs, it is crucial not to sugarcoat the situation. Treat your team members as adults and let them decide how to react to the information. This approach builds trust and respect. 

Resilience is the ability to bounce back from adversity. It’s a vital trait for leaders who face constant challenges. Building resilience involves mindfulness, compartmentalization, and mental agility. 

Practice Mindfulness 

Start your day with mindfulness exercises. Spend the first 10 minutes after waking up practicing deep breathing and focusing on one thing you want to accomplish for yourself. When possible, take detachment breaks every 30 minutes and compartmentalize your cognitive load by dividing your day into manageable blocks. These practices can significantly improve your recall, estress management, and work-life balance. 

Developing mental agility helps leaders handle stress effectively. When faced with a challenging situation, step back, breathe, and shift your perspective to see both the positives and negatives. This balanced view enables better decision-making and fosters a more resilient mindset. 

Embrace Diversity and Inclusion 

Inclusive leadership recognizes the value of diverse perspectives and fosters an environment where everyone feels seen, heard, and valued. Diverse teams, encompassing various genders, ages, and ethnicities, consistently outperform homogeneous ones. 

Nurture each team member’s growth by creating a positive employee experience, opportunities for engagement, and a supportive ecosystem. Develop programs like shadowing, join employee resource groups, and create opportunities for informal interactions such as coffee chats. Find mentors, sponsors, or executive coaches to provide feedback and strategies for skill development. 

Commit to Continuous Learning 

In a rapidly changing world, continuous learning is essential. Encourage formal, self-directed, and social learning within your team. Provide opportunities for in-person or online classes and create lunch-and-learn sessions. Show team members they are growing and improving, which not only enhances their happiness because of their positive contribution, but also makes them more marketable. 

Fostering a culture of continuous learning ensures that your team remains adaptable and innovative. Help them set learning goals, provide resources, and recognize their progress. By doing so, you empower your team members to take charge of their professional development. 


Leadership is an ongoing journey of making decisions that shape not only outcomes but also the experiences of those you lead. By embracing compassion, authenticity, resilience, inclusion, and continuous learning, leaders can create a supportive and thriving work environment. These qualities are not signs of weakness but of strength, fostering loyalty, engagement, and high performance. As a leader, your ability to navigate these attributes will determine the success and wellbeing of your team. Leverage Halloran’s strategic advising to transform your leadership and development challenges into opportunities for growth. Let us guide you through the intricate journey of bringing your product to market with confidence and strategic foresight while maximizing your leadership superpowers!  

To learn more about how Halloran can help you build your team and move your business goals across the finish line to success, contact us.  

Maximizing The Next 40 Years of The Orphan Drug Act 

This article is based on the session titled, “Sustainability of Rare Disease Drug Development,” at the DIA 2024 Global Annual Meeting, in San Diego, June 2024. Many thanks to the presenters: Darcy Frear (Bridgebio), Katherine Donigan (Sarepta), Karin Hoelzer (NORD), Patroula Smpokou (FDA), and Julia Tierney (FDA) for their valuable insights. This translation and the recommendations captured within is the author’s rendering of their points and should not be taken as exact quotations. 

Increasing Orphan Disease Drug Approvals: Strategies for Sustainability 

The passing of the Orphan Drug Act (ODA) in the U.S. in 1983 was a critical point for rare disease drug development, offering financial incentives through its Orphan Drug Designation Program and enabling scientific advances and approvals for rare disease drugs. Before the ODA was signed into law, approximately two drugs per year had been approved by the U.S. Food and Drug Administration (FDA) for rare diseases. Now, with 40 years since the ODA, hundreds of orphan drugs have been approved for use in the many diseases and conditions that are considered rare. In the past four decades, over 6,000 orphan drug designations were granted, and of those, 1,079 represent the development for rare diseases.1 

While the approval rate of orphan drugs has seen a significant increase, maintaining and further enhancing this trend requires strategic action. Current incentives such as grants, tax credits, market exclusivity, and the FDA’s Fast Track designation play crucial roles in the development over the next 40 years. 

Key Areas for Sustaining Orphan Disease Drug Development 

  1. Continuation of Successful Strategies: Accelerated Approval (AA) processes with surrogate endpoints must be sustained. This approach has been vital in bringing treatments to market faster, saving lives in the process. 
  2. Enhanced Collaboration: Increasing scientific discussions with the FDA through smaller working groups can advance the field. Incorporating diverse voices, including perspectives from patient advocacy groups, regulatory, scientific, and sponsors, is essential. 
  3. Policy Shifts: Moving from individual product approvals to advancing entire fields of products is crucial. Pilot programs should transition into full-scale applications, backed by robust policy and guidance documents. 
  4. Learning from the Past: Transparency about what works and what does not work is critical. The complexity of rare and orphan diseases requires a willingness to innovate and adapt based on past experiences. 
  5. Patient-Centric Approaches: Including the patient voice in the development process ensures treatments meet real needs.  

Addressing Obstacles and Leveraging Tools 

Reimbursement and approval obstacles hinder the development and availability of treatments. Utilizing all available tools for development and regulatory oversight, while maintaining flexibility, is vital for navigating uncharted territories. 

AA remains a cornerstone for bringing life-saving drugs to market. Contrary to misconceptions, AA still maintains rigorous scientific and regulatory standards. Future policies must continue to protect and optimize this pathway. 

Opportunities in Orphan Disease Drug Development 

  1. Collaboration with Regulatory Bodies: Enhanced cooperation between agencies like the Center for Biologics Evaluation and Research (CBER) and the Center for Drug Evaluation and Research (CDER) is crucial. Clear, adaptable rules are needed to incorporate new technologies effectively. 
  2. Early and Frequent FDA Engagement: Sponsors should engage with the FDA early and consistently throughout the drug development process. Sharing both successful and failed data can provide valuable insights. 
  3. Legislative Support: Protecting incentives under the Orphan Drug Act and the Inflation Reduction Act is essential. In addition, scaling up FDA pilot programs can address barriers more effectively. For additional insights, read: Rare But Not Forgotten: Opportunities in Rare Disease Drug Development or Preparing Now for the FDA’s START Program.  
  4. Breaking Down Silos: Greater alignment and collaboration within regulatory bodies can streamline rare and orphan disease drug development. Efforts to engage sponsors on efficacy endpoints and biomarkers are ongoing. 

Propelling Development Forward 

Emerging technologies, such as gene editing and next-generation sequencing, hold immense potential. Improved diagnostics and decentralized trial methods, including telehealth and Artificial Intelligence, can enhance patient outcomes and trial efficiency. Expanding platform approaches and manufacturing improvements will also help reduce costs and increase access to treatments. 

Halloran offers expertise in navigating the complex landscape of orphan and rare disease drug designation in regulatory affairs, clinical development, and strategic planning. By leveraging our deep understanding of the regulatory requirements and our proven track record of success, our clients enhance their chances of obtaining rare or orphan disease drug designation efficiently and effectively.  

Choosing Halloran’s experts means process efficiencies coupled with comprehensive support and guidance every step of the way, accelerating the path to market for their unique therapies and fast tracking the timeline for lifesaving treatments. To learn more about how we can help you, contact us.  


  1. Fermaglich LJ, Miller KL. A comprehensive study of the rare diseases and conditions targeted by orphan drug designations and approvals over the forty years of the Orphan Drug Act. Orphanet J Rare Dis. 2023 Jun 23;18(1):163. doi: 10.1186/s13023-023-02790-7. PMID: 37353796; PMCID: PMC10290406.  

Future of Clinical Trials: Forging New Pathways with Artificial Intelligence  

Biocom California’s first annual Converge Summit, recently held in South San Francisco, brought together life science leaders and executives to exchange ideas, foster collaboration, strengthen relationships, and spark innovation. When we think of innovation for this industry, the topic of Artificial Intelligence (AI) in clinical trials has steadily gained momentum, particularly around the opportunities and precautions that accompany its advancement. 

April Purcell, Clinical Development and Operations Consultant at Halloran, joined the panel, “The Future of Clinical Trials: Forging New Pathways Through Regulatory,” alongside other industry experts: Charles Fisher, Founder and CEO of Unlearn.AI, Ryan Moog, Head of Life Sciences Solutions at Datavant, Tim Scott, President and CEO of AustinPx, and Scott Skellenger, VP, R&D Informatics and Global Infrastructure Services at Amgen. 

Listening to this panel, four key insights resonated with me, particularly because we often field similar questions from our clients at Halloran on how best to leverage Artificial Intelligence in the clinical development lifecycle.  

How Do You Get New Technologies, like AI, Approved for Use in a Clinical Trial by the FDA? 

The U.S. Food and Drug Administration (FDA) remains committed to ensuring that drugs are safe and effective as new innovations in clinical trial technology continue to develop. As with any innovation, AI and Machine Learning (ML) create opportunities for efficiency and improvement while also presenting new challenges and risks. As such, the FDA has accelerated its efforts to create an agile regulatory ecosystem to facilitate innovation with patient safety at the forefront. We’ve seen this in their collaboration with the Center for Drug Evaluation and Research (CDER), the Center for Biologics Evaluation and Research (CBER), and the Center for Devices and Radiological Health (CDRH), particularly in their recent white paper published in March 2024, providing greater transparency regarding how FDA’s medical product centers are safeguarding public health while still fostering responsible and ethical advances with Artificial Intelligence in clinical trials. There is support, and the FDA has shown itself to be a true partner in the industry. 

That’s the key, though – responsible and ethical innovation. The panelists at the Converge Summit underscored this sentiment, echoing the importance of responsible and ethical innovation. April emphasized, “Clinical trial sponsors must focus on their data integrity and validation approaches, as well as develop a risk-management plan with their use of AI. The sponsor must have transparent processes and plans in place.” 

How Do You Validate AI-Enabled Tools for Use in Clinical Trials? 

April stated, “The unknown with AI tends to be around the results from the model. As a result, the sponsor must go through all the essential and critical validation steps to provide clarity to the FDA, including transparency around their validation processes and assessments, transparency with the model, and the results must be reproduceable.” 

The FDA is pinpointing that you need to prove your algorithm is accurate and reliable and validated from a compliance and clinical perspective. When you have all those steps in place, that’s when you’re able to validate your trial. 

In What Ways Can Trials Benefit from the Use of AI Technology? 

Can AI Really Assist with Inclusivity in Clinical Trials? 

Absolutely – the use of Artificial Intelligence in clinical trials has the proven ability to reach more diverse populations, enable targeted outreach for underserved communities, propel patient engagement, and even reduce bias in clinical trial design. The benefits are huge. 

One example is the use of Natural Language Processing (NLP) in the development of Informed Consent Forms (ICF) and other participant recruitment materials, which can help sponsors match the language and style to specific patient populations and remove barriers to reach a more diverse participant pool. This also works to the benefit of patients, increasing their access to clinical trials by offering a greater sense of trust and approachability.    

What is the Future of Clinical Trials with AI? 

“It’s certainly not possible to predict the future, but what I know is that everything and anything is possible in our industry. If we can dream it, we can make it happen,” shared April. The role of AI in drug development cannot be underestimated in the long term.  

If you are assessing your AI approach or don’t know where to begin, contact a member of our team today. We’re here to partner with you on your most pressing opportunities and challenges. 

Investors Follow Teams: Leadership Considerations to Enable Clinical Development Success 

Developing a life science asset from early discovery through clinical development to commercialization requires a clear clinical and regulatory strategy, adequate funding, relentless rigor, and most of all, an experienced and dedicated team. It is the people who drive progress, and it is the people that investors consider the most in their decision-making. Though this concept may sound dated, when leaders miss this core tenant, they may struggle to acquire the funding they need to meet their milestones to achieve clinical development success, and, as a result, they may risk seeing their progress dwindle. 

This important takeaway was also echoed during the MassBio State of Possible event and shared during the panel, “Science Moment: Rewriting What is Possible.” The panel discussed what enabled their success even in this choppy fundraising environment. Panelist Abe Ceesay, CEO of Rapport Therapeutics, noted, “Investors follow teams. If your team has a great track record, investors will take note and follow you. There must be a balance between great science and great teams.”  

We cannot agree more. Life science development companies must ensure they have the right people with the right expertise across key functional areas to ensure their success. Otherwise, they will be left with talent gaps that have significant consequences, including a lack of progress that may result in reduced funding opportunities and other downstream impacts.  

But what does the right expertise look like across an organization? In this article, we highlight a few leadership examples that showcase the value and importance of these key players to enable successful outcomes, creating a positive track record for future investments. 

Successfully Moving from Clinical Development to BLA Through Strategic Advising 

There are many circumstances that make or break clinical development success. Considering all the potential roadblocks, a small biotechnology company focused on immuno-oncology approached Halloran requesting a Development Program Manager to assist in their first Biologics License Application (BLA) submission to the U.S. Food and Drug Administration (FDA). 

In this example, the company had lost its Development Program Manager, cycled through multiple Vice Presidents of Regulatory Affairs, and very few team members held that critical BLA experience. Considering their personnel gaps, the company was poorly aligned, lacked proper planning, had insufficient executive support, requirements, and expectations were unclear, lacked resources, and their choice of technology did not enable them to achieve their internal goals. 

Halloran engaged the company by addressing the infrastructure challenges that prevented them from meeting submission goals. Halloran stepped in as the Development Program Manager and pivoted in essential ways. Halloran identified the following issues, and then worked efficiently to find appropriate solutions: 

Once Halloran fixed these challenges, the company’s efficient and organized infrastructure propelled them to a successful filing of their BLA with the FDA. This model became the gold standard for future development candidates in their portfolio. 

Enhancing Efficiencies and Reducing Risk with Clinical Development Leadership 

A small biotech developing an innovative therapy needed to retain a clinical trial leader as they launched their multi-center trial sites. The company experienced two cycles of leadership turnover, resulting in lagging strategy and operations. They needed to immediately hire an expert to drive progress forward, while they mindfully sought their full-time replacement. 

The company faced a tight timeline, minimal resources, and numerous inefficiencies. They chose to work with Halloran because of our expertise and ability to jump into operations and quickly get up to speed. They needed to slow down and focus on finding the right replacement, knowing an expert could stabilize and enhance their clinical operations and infrastructure to meet their next development milestone. 

Halloran provided the company with a step-by-step approach: 

As the short-term engagement ended, the client’s operations improved and noted enhanced and streamlined processes to propel the clinical trial strategy and observed better internal and external relationships with sites and vendors. While their clinical development program was back on track, their leadership had the time and space to find the right full-time replacement without rushing or risking their trial. 

Though there are many other examples to offer, these two come to mind because our team enabled progress for these companies to further drive clinical development success.  

Positive Impact of Collective Leadership Progress 

When a company leader hires the right functional leaders, the collective progress and momentum builds and continues to have a lasting positive impact on the company. As we’ve seen with investor behavior, the long-tail impact of that progress can be significant.  

If you have leadership and expertise gaps in any of your functional areas – clinical, quality, regulatory, and data and technology – please examine the pitfalls of those gaps and don’t delay these critical discussions. Halloran is here to support your goals and guide you through the intricate journey of bringing your product to market with confidence and strategic foresight. We understand the importance of a team and the significant impact that the right team can have on a company’s success.  

Raw Material Control for Biotechs (Part 2): Clinical Development Considerations 


This is part two of the Halloran Insights article on raw material control. Part one addressed the importance of establishing a level of raw material control at the earliest stages of product development. This article focuses on maturing the raw material control strategy in preparation for a commercial license application. The level of raw material control increases as clinical development progresses. This level of control is critical to achieving licensure of a therapeutic agent.  

As with part one in this series, the focus is on cell and gene therapies (CGTs). The actions described in this article generally apply to other types of early-stage biological therapies. 

Phases of Raw Material Control 

During phase one, clinical development quality assurance (QA) should review every Certificate of Analysis (CoA) associated with a raw material or consumable to confirm that the test results meet release requirements established by the manufacturer. If the raw material is derived from an animal source, then a Certificate of Origin (CoO) and TSE/BSE certificate should be obtained from the manufacturer. These certificates certify that the source material was obtained from healthy animals free of visual evidence of ill health. These certificates were described in part one of this series. 

During phase one clinical development, an identity test should be executed on every raw material used in the manufacturing process.1 A routine method for assessing the identity of raw materials and consumables is Fourier Transform Infra-Red Spectroscopy (FTIR). The instrument is not expensive relative to other standard analytical instrumentation (i.e., Liquid and Gas chromatographs) and can be applied to a broad range of raw materials and consumables. In addition, extensive libraries of Infra-Red spectra are readily available to serve as reference spectra.  

For compendial grade raw materials, identity testing is described in the respective pharmacopeial chapter. An alternate test method can be used if the alternative method is fully validated, suitable for use, and gives equivalent or better results than the official USP method.2 Evidence of this method validation must be available upon request and a summary may be provided to regulators to support the use of the alternate method.   

It is recommended that an appearance test for raw materials and consumables be executed upon receipt of the raw material or consumable that includes an inspection of the container/closure integrity and confirmation that the material meets the manufacturer’s acceptance criteria for product appearance (color, opacity, texture/form, etc.) Verifying container/closure integrity and appearance of the material is a valuable safeguard against using compromised materials and consumables in the manufacturing process. 

Consider using high quality raw materials at the outset of process development and certainly no later than phase one. Higher quality raw materials will typically cost more than research grade raw materials, sometimes substantially more. The use of research grade materials early in clinical development may make short-term economic sense but will not make long-term economic sense due to potential comparability concerns arising from the introduction of higher-grade raw materials later in clinical development. Therefore, whenever possible, replace Research Use Only (RUO) grade raw materials with higher-grade raw materials prior to launching clinical trials. Furthermore, to ensure comparability of pre-clinical drug product (DP) lots used in critical animal safety studies and clinical DP lots, it is best to make a critical raw material change before manufacture of DP for animal safety studies, thus mitigating potential FDA comparability concerns.3 

Before delving into regulatory and quality expectations for later phase clinical programs, please note that an abbreviated or expedited clinical development program does not translate to an abbreviated or expedited chemistry, manufacturing, and controls (CMC) development plan. The same standards and expectations apply towards manufacturing a therapeutic agent regardless of a traditional or expedited clinical development pathway. In the case of an expedited clinical program, the impact of choosing research or non-pharma grade materials to manufacture clinical material could potentially compromise the license application. Selection of such raw materials should be discussed with the regulatory authority prior to implementation. Expedited clinical development programs require careful planning and alignment to ensure that CMC deliverables (including establishing a licensable raw material control program) are on track. In this author’s experience, early-stage biotechnology companies when planning phase three and licensure activities, consistently underestimate the time and cost required to address CMC gaps. 

Phase 2 Considerations for a Raw Materials Control Program  

Developing a raw materials control program for phase two requires considerable foresight and planning. 

Determine clinical supply requirements for phase two and phase three trials. This information will drive the planning effort for scaling up the manufacturing process to meet clinical demand. Supply chain considerations are a critical aspect of this planning effort. Some raw materials and consumables may have limited availability, and process scale-up demand could exceed supply. Identifying and qualifying one or, possibly, more back-up suppliers (discussed later in this article) could mitigate this risk. 

Establish an implementation plan for raw material changes having a potentially significant impact on the manufacturing process and DS/DP critical quality attributes (CQAs). Changes to CQAs are likely to trigger a formal comparability study.7 The change implementation plan should include a list of new reagents, solvents, auxiliary materials, biological raw materials, and starting materials to be used in production of phase two clinical trial material. The plan should describe CQAs for each material needed to ensure manufacture of phase two and phase three clinical trial material that is consistent or better than that used in previous stages of development. Some of the CQAs for the proposed new material may not be captured on the manufacturer’s CoA. In such cases the Investigational New Drug (IND) sponsor may have to establish them in process development.  

The plan to establish new CQAs should include: 

Major changes to the manufacturing process in phase three are not recommended and, if comparability is not established, could introduce significant delays to the phase three clinical program and filing of the license application.  

During phase two, QA should begin to establish a robust vendor qualification program. If this program was launched for the phase one effort, prepare the program for the transition to phase three readiness (on site vendor audits, establishing a system for evaluating performance of raw materials from new suppliers when used in a pilot scale version of the manufacturing process, etc.) Assess the value of joining an organization that shares vendor audits, such as the Rx-360 consortium to supplement the audit program.9, 10  

The raw materials acceptance and release program should be expanded now. A key feature of this program is the raw material specification document which describes lot release test and acceptance criteria used by the manufacturer of the material. It also includes certificates required from the manufacturer (Certificates of Analysis (CoA), Certificates of Origin (CoO), TSE/BSE certification, etc.) as well as the results from in-house testing for raw material appearance, identity, etc. QA will use this document to verify that an incoming lot of raw material meets all lot release criteria and is accompanied by all required certificates. Once this information is confirmed by QA, the raw material is released for use in GMP manufacturing. Raw material specification documents are controlled documents subject to change control. They must, at minimum, be reviewed and approved by QA. This documentation should be set up no later than early phase two to ensure proper control of the raw materials and consumables used in the GMP manufacturing process. 

Establish identity and appearance tests for every critical raw material prior to the launch of phase two, as noted earlier. As phase two matures, establish additional testing requirements for critical raw materials to document CQAs identified as indicators of raw material performance in the manufacturing process. These tests and acceptance criteria will be added to the appropriate raw material specification document and evaluated as part of raw material lot release. 

If a phase one/two clinical trial design is proposed, then recognize that the raw material control plan may require modification. Identify raw material changes that must be made prior to initiating the phase three clinical trial as well as those that are nice-to-have. If possible, the critical changes should be introduced during phase one/two to secure a patient safety read out prior to entering phase three. No later than early phase one, execute a risk assessment to identify those changes which pose the greatest risk of triggering a comparability assessment (i.e., changing to a different cell culture media formulation, changing excipients used in DP formulation, etc.) If any of the nice-to-have raw material changes fall into the high-risk category, then consider deferring them to post-license process development. For the critical raw material changes that must be implemented during phase one/two, the sponsor should plan to execute a comparability study in early/mid phase one using pilot scale manufactured DP incorporating all the raw material and manufacturing process changes that must be made. Comparability will be based on a comparison of CQA data and stability data between DP from this pilot lot and the phase one clinical trial DP. Allow at least six months to collect/evaluate the data and receive FDA input on the study protocol and report. This estimate factors in delays inherent in communicating with the agency. Bridging safety studies will be required if comparability is not established.  

Evaluate the quality of incoming plasticware used in the manufacturing process. QA should do this no later than phase two. Plasticware that comes into direct contact with the DS or DP manufacturing process stream is subject to specific quality requirements. The vendor for the plasticware should confirm that the source polymer used to manufacture the plasticware has been tested for bioreactivity and meets USP Class VI plastics standards.11 Furthermore, the plasticware should have undergone an Extractables/Leachables (E&L) assessment.1215  

If the polymer used to manufacture the plasticware contacts organic solvents at any point in the manufacturing process, then compatibility of that polymer with that solvent should be documented. Verify that, at the temperature of the process step(s) where plastic encounters solvent, compatibility is maintained. A polymer may have an acceptable leachables profile in the presence of a particular solvent at ambient temperature but not at elevated temperatures.  

If E&L study data is not available for a plasticware item that contacts the process stream, then execute a risk assessment to determine if an E&L study should be executed for that material. Many contract testing labs offer E&L testing services. All safety-related information for plasticware should be described in the raw material specification document. 

Identifying and qualifying back-up suppliers of critical raw materials requires significant time and effort. Therefore, it should be initiated in phase two. Supplier qualifications will include a QA qualification (paper audit or site audit for critical raw materials) and a CMC qualification. The CMC qualification entails an assessment of the CQAs of the back-up raw material to ensure it is of comparable quality to the primary raw material. This assessment should include an evaluation of each raw material manufacturing process, including the source materials used, critical raw materials used, lot release tests for each raw material as well as the acceptance criteria for each quality attribute. The impurity profiles of the primary and back-up raw materials should be comparable. Before locking-in the back-up suppliers, evaluate the performance of the back-up materials in pilot scale manufacturing runs. This pilot scale material should be subject to the full panel of lot release tests and meet all acceptance criteria. Product obtained from the pilot scale process should be placed on stability. 

If a contract manufacturer is responsible for qualifying raw materials suppliers and manages the raw materials program for your manufacturing process, confirm that they are verifying the quality of the raw materials used in the DS and DP manufacturing processes. This can be assessed by reviewing their process for receiving, inspecting, testing, releasing, and storing raw materials and consumables (and retains) for manufacture of DS and DP. This would typically take place during the contractor qualification audit. Bear in mind that, from the regulators’ perspective, the IND sponsor owns the manufacturing process, even if it is executed by a contractor.18 Therefore, it is advisable for the IND sponsor to review quality certificates for every raw material and consumable used by the contractor to manufacture DS or DP. Executed batch records should include this documentation which should be made available during batch record review. The client should not assume that the contractor’s raw material control program is flawless. In this author’s experience a contract manufacturer, claiming that the client’s manufacturing process did not use animal-derived raw materials, did, in fact, use animal-derived raw materials. The regulatory implications of such an error can be significant if identified by FDA during an IND or New Drug Application (NDA) or Biologics License Application (BLA) review. Therefore, a comprehensive evaluation of the contract manufacturer, including a thorough QA audit, is essential to ensure that these gaps are identified early and mitigated. 

Phase 3 Considerations for a Raw Materials Control Program  

Establishing a raw materials control program for phase three should focus on preparing that program for licensure. It should include:  


This article has provided the framework for a raw material control program that can address the needs of each stage of clinical development. The reader is advised to be mindful of the quality and regulatory requirements for raw material control which will increase in scope and rigor as a company prepares for an NDA/BLA. 


  1. ICH Q7 Good Manufacturing Practice Guidance for Active Pharmaceutical Ingredients (2016) 
  1. FDA expects that sponsors of INDs will assess comparability of DP used in preclinical safety studies (especially the GLP tox study) with DP manufactured for clinical administration. The comparability assessment typically compares the two DS and DP manufacturing processes, including the raw materials used in these processes, the tests employed to measure DS/DP CQAs, lot release criteria, DS and DP stability, etc. 
  1. ICH Q5A(R2) Viral Safety Evaluation of Biotechnology Products Derived from Cell Lines of Human or Animal Origin (1999). While this reference is directed at cell bank manufacture, the principles of viral clearance/inactivation apply to other manufacturing processes.

  1. European Medicines Agency (EMA). “Guideline on Excipients in the Dossier for Application for Marketing Application of a Medicinal Product.” 19 June 2007. “It may be necessary to add tests and acceptance criteria to the pharmacopeial specification, depending on the intended use of the excipient (functionality-related characteristics)” 
  1. PDA Technical Report No. 56 (revised 2016), “Application of Phase Appropriate Quality System and cGMP to the Development of Therapeutic Protein Drug Substance (API or Biological Active Substance). While protein therapeutics are the focus of this report, the raw material control discussion is directly applicable to cell and gene therapies. 
  1. FDA Draft Guidance: Manufacturing Changes and Comparability for Human Cellular and Gene Therapy Products (2023). 
  1. FDA Guidance: INDs for Phase 2 and Phase 3 Studies: Chemistry, Manufacturing and Controls Information (2003) 
  1. “Raw material control strategies for bioprocesses”, G. Beck et al, BioProcess International, September 2009 

In 2009 the Rx-360 International Pharmaceutical Supply Chain Consortium was formed. Members include pharmaceutical, biotechnology and generic drug manufacturers along with suppliers, professional trade associations and regulatory agencies. The consortium’s mission is to “protect patient safety by sharing information and developing processes related to the integrity of the healthcare supply chain and the quality of its materials.” This organization offers members access to a library of audits for certain manufacturers and suppliers.  

  1. USP<88> “Biological Reactivity Tests-In Vivo”, USP 42 NF 37 
  1. Product Quality Research Institute Parenteral and Opthalmic Drug Product Leachables and Extractables Working Group Update: “Safety Thresholds and Best Demonstrated Practices for Extractables and Leachables in Parenteral Drug Products (Intravenous, Subcutaneous, and Intramuscular)” (09 September 2020) 
  1. BioPhorum Best Practices Guide for Extractables Testing of Polymeric Single-Use Components Used in Biopharmaceutical Manufacturing (April 2020) 
  1. BioPhorum Best Practices for Evaluating Leachables Risk from Polymeric Single-Use Systems Used in Biopharmaceutical Manufacturing (July 2021) 
  1. Extractables/Leachables standards have not been harmonized internationally as of December 2023. The International Conference on Harmonization (ICH) is developing ICH Q3E, a harmonized guidance for extractables and leachables. 
  1. 21CFR 211.65(a) 
  1. European Medicines Agency’s 2016 Guideline on process validation for the manufacture of biotechnology-derived active substances and data to be provided in the regulatory submission, Section 6.1.3 
  1. FDA Guidance: Contract Manufacturing Arrangements for Drugs: Quality Agreements (2016)