Explore every episode of the podcast The Effective Statistician - in association with PSI

Do you ever wonder what makes a presentation truly resonate with your audience? What turns a simple delivery into something unforgettable? In this episode, I tackle these questions head-on by exploring three key areas that every presenter must address: ethos, logos, and pathos. These timeless concepts, rooted in Greek philosophy, still hold incredible power today. By mastering them, you can boost your credibility, sharpen your message, and forge a stronger emotional connection with your audience. Join me as I reveal how these strategies can elevate your presentations and enhance your influence as a statistician.

Have you ever questioned how biostatistics and IT intersect, or why managing this relationship can feel so challenging? In this episode, I sit down with Pablo Joerger, a statistician who transitioned into programming after over 40 years in the pharmaceutical industry. We explore how the shift from mainframes to cloud computing has revolutionized our field and examine the pivotal role IT plays in supporting modern statistical analyses. If you're looking to better understand or improve your work at the intersection of biostatistics and IT, this episode offers practical insights and valuable takeaways.

Are you ready to elevate your statistical skills and network with industry leaders? Interested in presenting your research or learning from the best in the field? Curious about how a virtual conference can enhance your professional growth? This episode dives into the exciting details of the upcoming The Effective Statistician Conference, set to be our most interactive and diverse event yet. Chantelle, a PhD candidate in health data science and a vital part of our team, shares a preview of the wide variety of topics and innovative features planned for this year. From methodological insights to leadership training, our conference covers a broad spectrum of subjects presented by esteemed speakers from various organizations.

The field of statistics is rapidly growing, and statisticians play an important role in providing a competitive advantage to companies. However, finding the right job or candidate for a position can be challenging. That's where Clivoffective comes in - a collaboration between Clivolution and The Effective Statistician focused on connecting statisticians with career opportunities. If you're a statistician or hiring manager in the field, Clivoffective offers a personalized touch that sets it apart. Whether you're looking for a new career opportunity or seeking the right candidate for your company, Clivoffective has resources and expertise that can help make the process smoother and more efficient.  Join the Clivoffective Network to get exclusive access to networking opportunities and career development resources that can help take your career to the next level. In this episode, I explore together with Evelyn and André what Clivoffective has to offer and how it benefits both statisticians and hiring managers. We also talk about the following points:

In the field of statistics, we need specific skills necessary for being successfull. Debarshi Dey, currently the head of the Statistics and Programming and Data Management department at Morphosys, has spent the past 13 years in the pharmaceutical industry. With a PhD in statistics from UC Riverside, Debarshi believes that to be a "killer statistician," one must adopt the roles of a detective, lawyer, and storyteller. Debarshi and I discuss these key characteristics that make a statistician effective. We also explore these key takeaways from our conversation:

We statisticians have always been important for brining new therapies to patients. We design experiments, analyze and interpret data to provide valuable insights that can help make informed decisions. However, the value of our work increases if we're able to lead others.  But becoming an inspirational statistician requires more than just technical expertise. As you continue to grow in your career, don't forget to invest in yourself by learning from training programs, books, movies, and other resources that can help you become an inspirational leader. In this episode, Alun Bedding and I discuss how statisticians can become inspirational leaders and reach a higher level in their careers. We also explore suggestions and give additional insights on how statisticians can become leaders in their field.  Becoming an inspirational leader as a statistician requires a mindset change from technical proficiency to people skills. Leaders, by inspiring others, can help their and other teams grow and work towards the organization's goal. Building trust is key to becoming an inspirational leader. Alun and I also discuss these important points in order to level up your career and organisation:

Are you a statistician or data scientist looking to excel in your career and make an impact in the healthcare industry? Today's episode is inspired by a German podcast that delved into five key reasons for career failure and I fine-tuned this to fit statisticians.  As professionals working with complex projects and tight deadlines, it's important that we recognize these pitfalls before they cause irreparable damage to our success. Join us as we explore each of these five potential hazards, discuss why they have such potential for harm, and learn from engaging expert advice on how best to prevent or overcome them:

If you're a statistician, data scientist, or programmer looking for quality training opportunities that will help you advance your career, you might want to look into The Effective Statistician Academy. This exclusive academy offers a range of courses that cover essential topics in the field of statistics. From leadership to innovation, knowledge, and excellence, you're sure to find a course that fits your needs and goals. The Effective Statistician Academy offers four distinct areas of training: Leadership, Innovation, Knowledge, and Excellence. Each area features expert-led courses that are designed to help you gain the skills and knowledge you need to succeed in your career. Whether you're looking to take your leadership skills to the next level or stay up-to-date on the latest innovations in the field, the Academy has you covered. In this episode, I will discuss more the key features of the Academy, the topics it will cover, the top-notch speakers who have extensive experience and in-depth knowledge of the subject matter, and why you won't have to break the bank to take advantage of this exciting opportunity.  I also talk about the following points:

What strategies do you use in your work as a statistician to ensure successful outcomes? How do you set expectations with stakeholders when tackling a project? Are there any common mistakes statisticians make when setting expectations in their job that you have learned to avoid? How setting realistic expectations can positively impact your work as a statistician? As I embark on this journey of discussing expectations, it reminds me of an incident that happened to me recently. During one of my business trips, the coffee I ordered at an airport was quite enjoyable; however upon opening the cup - much to my dismay - only half filled with liquid gold! The size and shape established a certain expectation for what should be inside which created feelings of dissatisfaction due to unfulfilled hopes. It goes without saying that if they would have had appropriately sized cups, then there wouldn't have been any misalignments in regard to meeting expectations. Fascinating how something as small scale such different outcomes can make or break experiences! As statistical professionals, we frequently encounter situations where our technical expertise is required to communicate complex data insights to a non-statistical audience. Creative data visualizations, tailored to the audience, are an effective tool to help us overcome this communication gap. By presenting information in a clear and understandable manner, we can over-deliver expectations and make a real impact on our work projects. In this episode, I give more tips on how to set expectations and the following points:

As statisticians, we rely on good quality from programmers and data management. And if you talk to your colleagues, everybody has a story about a poor experience. But the questions are: How do we collaborate with other departments to create a quality deliverables? How to strike the right balance between working on processes and managing people for maximum efficiency? How to we take ownership and drive responsibility to learn from mistakes and not blaming each other? Tension often arises between statisticians, programmers, and data managers when it comes to delivering quality products in a timely manner. In this episode, Benjamin and I discuss how you can maintain a high level of quality that satisfies everyone. We talk about the importance of good communication. We discuss the balance between processes and people. While sophisticated processes may be necessary, relying too much on documentation can lead to missed opportunities or overlooking potential solutions. Listen to this episode now while we dive deep into these points below:

What knowledge gaps exist regarding the implementation of these new analytical techniques, and how can statisticians and data scientists bridge them to maximize effectiveness of clinical research? Despite the promises of Bayesian approaches, the lack of expert training, software tools, and computational resources has made their adoption slow. Statisticians and data scientists should invest in training programs to enhance their skills in Bayesian modeling, use open-source software for Bayesian modeling, and ensure that they have access to well trained computational analysts.  It is also essential that statisticians and data scientists effectively communicate the results of these analyses to clinicians, regulatory authorities, and maybe even patient groups to encourage adoption. Bayesian approaches have great potential to improve the accuracy and efficiency of data analysis in early-phase clinical trials. But Bayesian methods are not without their challenges, but with adequate training, resources, and communication, they provide opportunities for novel ways to cope with complex problems in clinical research. But, first comes the challenge: prior elicitation from clinical information. Developing prior distributions can be difficult without the right set of tools and resources. In this episode, Miguel Pereira, a statistical consultant for a German-based company COGITARS specializing in early clinical trial design, and I highlighted ways to tackle these challenges. We also discuss the following points:

For years, creating data visualizations has frustrated statisticians, data analysts and data scientists. Software - especially SAS - hasn't been great and organisation have tried to take the pain out of the process by creating standard figures.   But these standard graphics fail to communicate the message to the intended audience in the best way. Great data visualisations consider the needs of an audience in terms of language, understanding, and context, as well as the communication channel and the message to be conveyed. With so many elements to take into account, the design space for visualisations can be overwhelming with factors such as color, filtering data, animation, and uncertainties all coming into play. Unfortunately, many senior people in large statistics organizations focus only on regulatory requirements and don't invest time in understanding the importance of visualizations. In this episode, I discuss why it is difficult to create a great standard data visualization and what organizations can do to improve their data visualization game.

Have you been considering a one-armed observational study?  As a statistician, it is important to understand the various types of studies that are used in data gathering. In this episode, we will be discussing one-armed observational studies and why they are, in most cases, not a good idea. We will also touch on the early days of my career as a statistician and how I initially approached one-armed observational studies. We also discuss the reputation problems of these studies and the scientific problems such as:

Have you ever wondered how project management and collaboration between statisticians and clinical operations professionals impact clinical trials? What challenges do they face, and how can they ensure high-quality, timely, and budget-conscious results? Today, I’m thrilled to have Jessica Cordes with us. Jessica brings over 15 years of experience in clinical operations, particularly in oncology and cell and gene therapy. She founded her own consulting company, helping small to mid-sized companies with their clinical trial needs, and she launched a digital training academy to share her extensive knowledge. In this episode, we dive into the intricacies of project management and collaboration, exploring how effective communication and detailed planning can significantly enhance the synergy between these crucial functions in the clinical research landscape. Tune in to gain valuable insights!

The world of healthcare continues to change, and it’s important to keep up with the latest advances in technology and research. That’s why I'm excited to talk with Shirley Wang, one of the leaders of RCT Duplicate, a study focused on duplicating randomized clinical trials through real world data.  She is currently leading the RCT Duplicate as the first author on some key publications related to the initiative. She has been instrumental in helping move the project forward by analyzing data from various sources and developing new methods for collecting information from real-world settings. Her work has helped pave the way for more reliable findings based on real-world evidence—which will ultimately benefit everyone who works in healthcare.  In this episode, we discussed RCT Duplicate's goals and recommendations for real-world evidence researchers based on findings from the initiative. We also discuss the following points:

Today I'm talking with Rachel Tham, a principal statistician, about a book that has been incredibly impactful in both of our lives—Deep Work. We discuss what deep work is and how it can help statisticians at work.  Deep work is a concept developed by Cal Newport which encourages people to focus intensely on one task for an extended period of time without any distractions. This type of focused work allows people to produce higher-quality results in less time than if they were trying to multitask or do shallow tasks. Join us and learn more about deep work concepts and how they can improve your productivity and satisfaction. Rachel and I discuss the following points:

Why are companies often running single arm studies in development?  What are the potential drawbacks and why is it not a binary choice between full comparative study and single arm trial? What are solutions in between to find a balance between feasibility and rigour? Single arm studies are a popular method for collecting data despite being critiqued for decades. It is a type of research design in which the investigator only observes one group of participants over time.  This design is often used when sponsors claim it would be unethical to randomise patients into different groups or when comparing two treatments would be too difficult.  However, there are several drawbacks associated with single arm studies. First of all, bias can easily creep into the results. Anja Schiel - the most recognised regulatory statistician in Europe -  and I discuss the potential drawbacks of running single arm studies, as well as ways to balance scientific rigour with feasibility. Tune in while Anja and I give some of the great advice we have come up with. We also discuss the following points:

Reproducible research is a key part of research in the pharma industry. It allows for transparency, understanding, and accuracy in the research process. But how can you make your research more reproducible? Today, I talk with Heidi Seibold who has dedicated her career to helping researchers become more reproducible. Let's take a look at 3 steps that she recommended for making your research more reproducible:

Are you a statistician working in the pharmaceutical industry and never got in touch with economic modelling and network meta-analyses? Then you should listen to this episode! The EU HTA will not only affect all statisticians in the pharmaceutical industry with respect to skill sets and collaboration (we talked about that in podcast #3), but will also have impact on the economic modelling that is needed for the reimbursement and pricing decisions in many European countries. Understanding the influence of the joint clinical assessment on the economic modelling, the relationship between estimands and PICOs as well as the pre-specification of statistical analyses and their use in economic modelling is becoming much more important for statisticians in the near future. In this episode, we will talk about role of economic modelling in the HTA process, and the influence of the EU HTA and the corresponding statistical analyses on that process.

All statisticians in the Pharmaceutical Industry will be impacted by the new EU HTA regulation. Activities around HTA submissions will happen earlier than currently, in parallel to the regulatory approval process for marketing authorization. There will be an increased scope of evidence for the joint clinical assessment to fulfill the needs of all EU member states, and so there will be a large package of statistical analyses that need to be provided in addition to the submission to the regulatory bodies. This will redefine how you, as a statistician, work, and with whom you need to collaborate. Both HTA and clinical development statisticians will need to join forces to define the value story for the complete lifecycle of the drug. HTA specific analyses will need to be planned in parallel with clinical development. In this episode, we will discuss the future skill sets that statisticians in the pharmaceutical industry need to adopt with the new EU HTA regulation being applied in 2025 already.

If you’re a statistician working in a regulatory setting, you’re probably familiar with estimands as a way to frame the clinical question of interest. But what’s the role of estimands beyond regulatory approval, in a Health Technology Assessment setting? That question is especially important these days where the framework for pan-European HTA is taking shape. In this episode, we’ll touch on some HTA body views around estimands, and reflect on how current draft guidelines for EU HTA do and don’t address estimands.

Are you a statistician, data scientist, or healthcare specialist looking for the perfect conference to attend? The Effective Statistician Conference 2023 is an exciting opportunity for statisticians, health care specialists, and data scientists to come together and learn from industry experts, exchange ideas, share breakthrough advancements in statistics, collaborate with peers, and stay ahead of the latest trends. This virtual event will happen on the 25th of April and the registration is FREE. Through comprehensive talks delivered by influential and seasoned professional speakers across many disciplines – statistics across the R&D phases, process optimization, data visualisation, leadership, simulation, ... – attendees can make meaningful connections that help them become more effective problem-solvers in the ever-evolving digital age. This highly anticipated event is sure to leave everyone inspired and well-equipped with newfound knowledge ready to apply to their practices. Let's revolutionize how statistics can drive innovation! In this episode, I'll be discussing these points in detail:

As a statistician, have you ever wondered—why are statistical analyses for HTA dossiers differ from those in regulatory dossiers? Aren’t they both just benefit-risk assessments? In this podcast, we review some of the history and background of how HTA and regulatory decision making have common sources of information, but different utility functions for how they use that information. Why have we had a common European regulatory framework, but not a common HTA framework—until the near future. And what is the EU HTA Regulation? Why has it been established, what does it hope to accomplish…..and why does this matter to statisticians working in the pharmaceutical industry? This podcast is the first of a series of 4 exploring the role of statisticians and statistics in HTA analyses, and how the new European HTA Regulation that will first start being applied to medicinal products in 2025, will impact statisticians working with clinical (and non-clinical!) data to support and evaluate HTA decision making. Learn how you can get more involved in shaping the future of EU HTA as a statistician at the local and regional level.

Have you ever wondered how we make crucial decisions in the early phases of clinical trials? How can a Bayesian framework enhance these decisions? Today, I talk with Audrey Yeo from Roche to answer these questions. Fresh from the PSI conference, Audrey, a seasoned statistical software engineer, introduces us to an innovative R package designed for early-phase clinical trials. This tool promises to revolutionize decision-making with its Bayesian approach. Join us as we explore the development, features, and impact of this groundbreaking tool, and discover the collaborative efforts that drive its evolution.

Are you curious about aggregate safety assessment planning? Whether you’re an experienced statistician or just starting out in the field, your work increasingly demands that you apply principles of aggregate safety assessment planning. With an ever-changing and advancing landscape filled with data and technology advancements, it is essential to stay current on this topic. In this episode, Greg and I explore what aggregate safety assessment planning is, its components, its importance for statistically informed decisions, and how it ties into patient safety initiatives. You will be equipped with a better understanding of the fundamentals so that your efforts can make powerful contributions in research settings and support meaningful health outcomes for patients everywhere. Stay tuned while we discuss the following key points:

Anyone can create a data visualization but not everyone can create a data visualization that is effectively communicating the data – and this is what we should aim for. Done wrong they leave the audience confused. In this episode, I’ve gathered up six problems around creating data visualisations, so you can improve the quality of your visualisations. Stay tuned while I talk about these 6 problems:

A few days from today, it will be Christmas already and I am sure you are very thrilled to get ready for Christmas! And it's almost time for another year and as the New Year brings a lot of challenges, I am excited to share with you my plans and projects for 2023 that you and I both will definitely benefit from and these events and projects will surely help you achieve more with your personal growth and especially, your career growth at the same time. Tune in while I discuss the following exciting events and plans:

Do you want to be a more effective statistician? Do you have what it takes to be an effective leader in your organisation? Many people think that strong leadership skills are something that statisticians don't have. However,  as a statistician, you definitely have a lot to offer an organization. Statisticians often have the skillset required for leadership positions as they can use their questioning and decision-making abilities to help solve issues within an organization. In this webinar, we will discuss how statisticians are in fact very gifted with unique leadership skills that can make them more influential and successful. We identify these skills and discuss how you can leverage them to become a more influential and effective statistician. Listen to this episode now and learn from the following points we discuss:

What are the advantages of being active on LinkedIn? How can you find the right career opportunity on this social site? How can increasing your network attract more opportunities? What kind of content should you post? In today's episode, I am talking about my favorite social media platform, LinkedIn. LinkedIn has helped a lot of professionals not only to meet new people and to broaden their network but also, in discovering new skills, learn new insights, and get motivation. Listen to this now and learn how to maximize the use of your LinkedIn account. I also discuss the following points:

Why is it important for a statistician to take the culture of the first mover advantage on a more personal level? How do the first-mover advantages help the personal and professional growth of a statistician? What does it take to be the first mover? How does being the first mover solve problems early? How do you develop the motivation to be the first mover? In this conversation, we talk about the effective impact of the first-mover advantage. To give a more visual distinction of this strategy, it is more like a chess game where the first mover often decides the direction of the game. In statistics, this attitude offers a more effective sense of understanding what the first move culture is all about. Here are some of the lessons that are presented in this conversation:

How could differences between countries affect the elements that are included in statistical research? How could studies with such a diverse sample from different countries be managed to create a more dependable reference for statistical studies? How do differences of the quality of care that the target population receives impact studies? As statisticians, we need to be able to understand the validity of the outcomes of statistical analysis for different target populations. In this podcast, you will learn ways to tackle this problem: In this podcast, you will learn how this problem could be resolved:

Leadership is one of the most important aspects of any organization, and statistics is no exception. Good leadership can help a field grow and shape the future, while bad leadership can lead to stagnation or even ruin. In this episode, we discuss what leadership means for statisticians, how we develop our own leadership style, and how it helps us continue to move forward in our careers. Join Alun Bedding and me while we answer these questions: What made Alun decide to focus on leadership? What are the advantages of practicing good leadership for statisticians? How to be an effective leader and motivator? How did Alun and I got equipped in training others to be effective leaders? We also talk about the following interesting points:

Are you struggling with your presentations? How does storytelling increase the interest of your listeners? How does audience relatability help in improving the way you are able to connect with them effectively? How does establishing rapport with your audience affect the overall value of your message and how it is going to be used by your target listeners? How can you effectively anchor a message to a visual element through storytelling? In this conversation with Helen, we discuss the importance of storytelling in creating relatable presentations that will have a more personal impact on the listeners. Rapport and connection with the audience are critical to the way a message is received. Here, Helen Packham explains more about this issue. Here are some lessons you can get from this episode:

Does Multi-tasking help or harm you? How could you handle the desire to multitask more effectively? What fallacies about multitasking does the world currently believe? Are there ways to be more productive other than multitasking? How does focus change the way we function in any form of industry? This podcast gives our listeners an idea of what multitasking is, how it has changed the way people work through time, and how it has created more problems than solving issues as expected. The information we share in this podcast will help you become more productive and understand the application of multitasking in a much better light. Here are some lessons we want to impart through this podcast:

Are you looking to elevate your career as a statistician? Curious about how accreditation can enhance your professional status and build trust in your expertise? In this episode, I talk with Magnus Pettersson about the FENstatS accreditation process, an initiative by the Federation of European National Statistical Societies. Magnus shares his insights on the significance of accreditation and the rigorous yet rewarding process involved. Join us as we explore how this accreditation helps statisticians demonstrate their expertise, uphold ethical standards, and build trust in our profession, especially in the evolving landscape of data science and artificial intelligence. Tune in to learn how you can achieve FENstatS accreditation and take your career to the next level!

In this last part of the leadership series with Gary Sullivan, we talk about the next steps, you can take to work on your leadership skills. We cover the following areas: - Books - Mentoring - Role of supervisors - Podcasts - Mastermind groups - Courses

Indirect comparisons and network-meta analyses play a rising role in our world. A pubmed search provides 240 hits for the term network meta-analysis in 2011. This increased to 3223 in ten years later 2021 – more than 13 times more! There are many problems you can solve using these approaches and statisticians overlook some on a regular basis. Don’t miss out on providing your colleagues with great evidence (and with the ability to learn a lot about this interesting statistical approach). Listen to my short but informative discussion with Daniel Saure as we explore five different cases with which network meta-analyses are extensively affected. Our conversation defines the problem and solutions regarding these three primary cases:

In this second part of the interview with Gary, we speak about the building blocks of leadership without authority from a statistician’s perspective. We cover questions like: Is influence the same as power? What is the role of trust, what are the different elements of trust and how can we improve trust being technical experts? How can we build relationships at work, that help us to influence change? Is influence through relationships only relevant “sideways” or also “upwards” and “downwards”? How do we know with whom we need to invest in building relationships? Is there a way of assessing how good our relationships are?

How does information technology help reduce the statistical margin of mistakes? How does leadership come into play when creating programs designed to effectively manage statistical data? How does open-source culture in informatics development in statistics help in creating innovative technology to increase research validity? Does open-source development change the way statistical validation is treated especially in developing new forms of health treatment? My interview with Coline Zeballos of Roche informatics will give you an idea on how the development of Open-Source culture in developing applications that will help validate data collected for statistical research is actually changing the way medical studies are being completed and applied by pharma companies today. Coline also shared her thoughts about internal leadership in this podcast, which will be useful not only for statisticians but for professionals in other industries as well. Some of the lessons you can get from this podcast include:

What makes persistence one of the most important factors of being a leader? How does persistence among leaders in statistics affect the results of their work? How could persistence translate into understandable and actionable results for the target population? How can a persistent leader bring high value to bringing change to the target population? How does clear vision help leaders develop persistence in reaching their goals? Even in the face of difficult barriers, a persistent leader does not give up. This short but rich conversation between Gary and me introduces the meaning of leadership and how persistence shapes its value. Looking into the examples of Martin Luther King and Earnest Hemingway, this podcast will teach you how history proves that persistence among leaders go a long way in promoting change and development across the globe. Learn from me and Gary as they talk about persistence and how it can make leadership among statisticians more effective as they translate the results of their studies to the target population. Here are some key lessons you can learn from this episode:

The Leadership program is now open and in this bonus episode, we go into some key questions about statisticians and leadership that may help you decide on your next steps. Here are the following key questions:

How do real-world data variables change the overall value of a clinical study? How does clinical study make it to the implementation stage and how is this strengthened through the use of RWEs? How does Real World Evidence validate the data and results that are presented in clinical trials? The extensive existence of Real World Evidence resources is already out there and is ready for utilization in clinical trials. In this second part of the discussion between Josephine and Alexander, we highlight how, from the point of validation to implementation, RWEs work well in strengthening the foundation of every study approved for actual real-life application. Here are some of the key learnings you can gain from this episode:

Getting things done through others is a key part or even the definition of leadership and her clients face often the same situation as statisticians. They need to convince people rather than command them. In this episode, we have our first non-statistician as a guest. Julia has built her own consulting and training company Zestfor. She and her team specialise in developing Training programmes and resources scientifically tailored for technical markets – including Pharmaceutical, IT, and Life. In this episode, we cover the following topics:

What makes a statistician more valuable to an organization? How does a statistician’s work culture differ from working in a large company to working with a smaller organization? Would statisticians be able to bring more value to their work, especially when working with smaller companies? When the term “statistician” comes to mind, it is easy to picture a person who sits for hours behind a desk working with numbers and mathematical analysis. However, there is something more to statisticians than what actually meets the eye. More than just the expectation of a person being a brilliant person who understands numbers better than the average individual. The truth is, statisticians are the ones who have the capacity to bring change to the table, especially because they know what the numbers are telling them. In this episode, Kim and I talk about how statisticians become the big fish in a small pond when they work with smaller organizations. Here are some key learnings you may be interested in as you listen through this episode:

In this podcast episode, we discuss an important part of leadership – proactive behaviour. Or simply put—drive! As a statistician, your day-to-day approach to this topic will build up to long-term success. We discuss various aspects of the drive including:

Do you ever wonder how networking can boost your career as a statistician? Are you an introvert who finds the idea of networking daunting? In this episode, I explore the essential skill of networking and why it's crucial for professional success. Despite the challenges many of us face in social settings, networking offers significant benefits that extend beyond the office. I share practical advice on how to initiate and maintain professional connections, both within and outside of your organization. From casual lunch meetings to attending conferences and joining professional associations, I provide a comprehensive guide to help you enhance your career through effective networking strategies. Tune in to discover how you can leverage networking to gain insights, seize opportunities, and ultimately become a more effective statistician.

What are RWEs or Real World Evidence about? How are Real World Evidence used in determining the value of clinical trials on how they are applied in real-life settings? How are RWEs validated and how are they used in actual medical cases as healthcare procedures are applied in hospitals? What variables tend to affect the way RWE data is managed and used as a reference to actual medical developments? How does accurate reporting affect the value of collected RWE data? Clinical trials accomplished to support the development of healthcare industries around the globe are critically defined to the references on how health conditions are diagnosed and treated. In the end, the real target end-users of the medicines and other medical procedures are the patients. Hence, creating a more patient-centered approach in handling clinical trials is an important part of defining the success of one study. One way of making sure that the clinical trials reflect real-world situations is through inculcating Real World Evidences or RWEs. Often, these evidences are garnered through observing samples that are free from the manipulation of the researchers. Through EHRs or Electronic Health Records, statisticians are able to collect data without necessarily influencing the sample population that they have chosen to observe. How does the FDA consider these factors of evidence? Listen to Josephine Wolfram, an expert in RWEs, and me, and learn more about the way the FDA sees the value of RWEs and how this factor affects the overall procedures considered when approving new medicines and medical procedures that are offered for patients to consider. Here are some key takeaways to look forward to when listening to this podcast:

In this episode, we share out ideas and experiences, which mindset sets up statisticians for success. We cover topics around:

How does patient adherence affect the results of clinical trials? Are there ways to improve patient adherence to medication and treatments not only in clinical trials but also in real-life situations? What is the future of the value of clinical trials in terms of inclusive technological innovations? Clinical trials are designed to test whether a medication would be best for the target population. While these approaches are considered critical to healthcare development strategies, their value for applicability still remains dependent on how the participants cooperate with the process of treatment which involves their attitude towards adherence to the trial. In this podcast, join me and Lina as we talk about the most effective ways to get patients to adhere to treatments they are offered in clinical trials. With her background in psychology, Lena’s insight is on point especially when it comes to determining the role of human behavior in terms of determining the applicability of the results garnered from clinical trials. While there are several problems that arise from the lack of patient adherence, this podcast highlights some of the most effective ways that are available today for researchers and statisticians to consider when handling patient-centric clinical trials-therefore ensuring a high rate of patient adherence. Here are some of the important learnings you can get from this episode: