{"id":1014,"date":"2025-11-19T04:58:00","date_gmt":"2025-11-19T04:58:00","guid":{"rendered":"https:\/\/pharma-talks.com\/?post_type=episode&#038;p=1014"},"modified":"2026-09-08T08:04:35","modified_gmt":"2026-09-08T08:04:35","slug":"ai-driven-pharma","status":"publish","type":"episode","link":"https:\/\/pharma-talks.com\/episodes\/ai-driven-pharma\/","title":{"rendered":"Alejandro Jaramillo: Analytics as GPS, Not Rearview Mirror\u00a0"},"content":{"rendered":"\n<div style=\"height:200px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<style id=\"pharmatalks-content-section-style\">.pt-content-section{background:var(--pt-content-section-bg,transparent);color:var(--pt-content-section-text,var(--color-text));padding:var(--pt-content-section-padding-top,32px) var(--pt-content-section-padding-x,0) var(--pt-content-section-padding-bottom,32px)}.pt-content-section 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var(--pt-content-section-mobile-container-padding-bottom,var(--pt-content-section-container-padding-bottom,0))}}<\/style>\n<section class=\"wp-block-pharmatalks-content-section pt-content-section\" style=\"color:#082480;--pt-content-section-padding-top:32px;--pt-content-section-padding-bottom:32px;--pt-content-section-mobile-padding-top:16px;--pt-content-section-container-max-width:1240px;--pt-content-section-container-padding-top:0px;--pt-content-section-container-padding-bottom:0px\"><div class=\"container\">\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/pharma-talks.com\/wp-content\/uploads\/2026\/09\/Pharma-Talks_-DATA-DRIVEN-PHARMA-IN-THE-AGE-OF-AI-1-1.png\" alt=\"\" class=\"wp-image-1015\" width=\"1200\" height=\"675\" srcset=\"https:\/\/pharma-talks.com\/wp-content\/uploads\/2026\/09\/Pharma-Talks_-DATA-DRIVEN-PHARMA-IN-THE-AGE-OF-AI-1-1.png 1200w, 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class=\"wp-block-pharmatalks-episode-player pt-episode-player\" style=\"color:#082480;--pt-episode-player-padding-top:0px;--pt-episode-player-padding-bottom:0px\"><div class=\"container\"><div class=\"pt-episode-player__inner\"><div class=\"pt-episode-player__media\"><img decoding=\"async\" src=\"https:\/\/pharma-talks.com\/wp-content\/uploads\/2026\/02\/pt-logo-1.webp\" alt=\"Don\u2019t miss a new episode\" loading=\"lazy\"\/><\/div><div class=\"pt-episode-player__content\"><p class=\"pt-episode-player__subtitle\">Alejandro Jaramillo: Analytics as GPS, Not Rearview Mirror\u00a0<\/p><h3 class=\"pt-episode-player__title\">Don\u2019t miss a new episode<\/h3><div class=\"pt-episode-player__controls\"><button type=\"button\" class=\"pt-episode-player__play\" aria-label=\"Play\" aria-pressed=\"false\"><span class=\"pt-episode-player__play-icon\" aria-hidden=\"true\"><\/span><\/button><div class=\"pt-episode-player__panel\"><div class=\"pt-episode-player__timeline\"><input type=\"range\" class=\"pt-episode-player__progress\" min=\"0\" max=\"100\" step=\"0.1\" defaultvalue=\"0\" aria-label=\"Seek\"\/><\/div><div class=\"pt-episode-player__bottom\"><div class=\"pt-episode-player__actions\"><button type=\"button\" class=\"pt-episode-player__speed pt-episode-player__speed--down\" data-speed=\"down\" aria-label=\"Slow down\"><span class=\"pt-episode-player__speed-icon\" aria-hidden=\"true\"><\/span><\/button><span class=\"pt-episode-player__speed-display\">1X<\/span><button type=\"button\" class=\"pt-episode-player__speed pt-episode-player__speed--up\" data-speed=\"up\" aria-label=\"Speed up\"><span class=\"pt-episode-player__speed-icon\" aria-hidden=\"true\"><\/span><\/button><\/div><div class=\"pt-episode-player__time-volume\"><div class=\"pt-episode-player__volume\"><button type=\"button\" class=\"pt-episode-player__volume-toggle\" aria-label=\"Mute\" aria-pressed=\"false\"><span class=\"pt-episode-player__volume-icon\" aria-hidden=\"true\"><\/span><\/button><input type=\"range\" class=\"pt-episode-player__volume-range\" min=\"0\" max=\"1\" step=\"0.01\" defaultvalue=\"1\" aria-label=\"Volume\"\/><\/div><div class=\"pt-episode-player__time\"><span class=\"pt-episode-player__current\">0:00<\/span><span class=\"pt-episode-player__divider\">|<\/span><span class=\"pt-episode-player__duration\">&#8211;:&#8211;<\/span><\/div><\/div><\/div><\/div><\/div><div class=\"pt-episode-player__links\"><a class=\"pt-episode-player__link\" href=\"#subscribe\" rel=\"noopener noreferrer\">Subscribe<\/a><\/div><audio class=\"pt-episode-player__audio\" src=\"https:\/\/pharma-talks.com\/wp-content\/uploads\/2026\/09\/fixed_AI-Driven-Pharma_-Turning-Data-Into-Discovery-Pharma-Talks.mp3\"><\/audio><\/div><\/div><\/div><\/section>\n<\/div><\/section>\n\n\n\n<section class=\"wp-block-pharmatalks-content-section pt-content-section\" style=\"color:#082480;--pt-content-section-padding-top:32px;--pt-content-section-padding-bottom:32px;--pt-content-section-mobile-padding-x:20px;--pt-content-section-container-max-width:1200px;--pt-content-section-container-padding-top:20px;--pt-content-section-container-padding-bottom:20px;--pt-content-section-container-padding-x:20px\"><div class=\"container\" style=\"border-radius:20px;overflow:hidden;background-color:#ffffff\">\n<p class=\"wp-block-paragraph\">Data used to describe what already happened. The shift underway is toward data that shapes what happens next \u2014 and the organizational change that requires is larger than the technical one.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In this episode of Pharma Talks, Nataliya Andreychuk spoke with Alejandro Jaramillo, whose career spans data analytics, commercial strategy, and medical functions at Novartis, Johnson &amp; Johnson, and Ipsen.&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>From Dashboards to Decisions<\/strong>&nbsp;<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">When Alejandro started in the field, most of the work looked backward \u2014 establishing what had happened and building relationships around that understanding. The current work is analytics driving strategy, which means predicting rather than explaining, and surfacing both opportunities and problems before they resolve themselves.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">His framing: analytics as &#8220;a GPS for the business \u2014 helping on the journey of discovery.&#8221;&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">He&#8217;s careful about the novelty claim. Much of what gets called AI and machine learning builds on methods that already existed. What changed is scale and speed.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Nataliya&#8217;s extension of the metaphor is the practical one \u2014 everyone needs enough data fluency to be a skilled user of results. &#8220;We are all GPS users in the end.&#8221;&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Value and Hype<\/strong>&nbsp;<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">&#8220;We work a lot with modular content and omnichannel journeys, and what I see is that AI in life sciences can bring huge value, but only when the business question is clear. It&#8217;s not magic,&#8221; Nataliya said.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Alejandro returned to GPS to make the same point. &#8220;With a GPS, we can go anywhere, find any location \u2014 it&#8217;s amazing. But it&#8217;s both a journey and a destination.&#8221; AI is a set of systems for processing information, reasoning, and deciding at scale \u2014 which means the value depends entirely on knowing what you&#8217;re trying to accomplish with it.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">His formulation of the limit: AI won&#8217;t replace thinking, but it will change how thinking happens.&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Where It&#8217;s Working, and Where It&#8217;s Risky<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">He points to biopharma applications in sales performance, prediction accuracy, and patient adherence, with further work in R&amp;D, drug development, and clinical trial optimization.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The caution comes with it. &#8220;We sometimes expect perfect predictions, but we must remember the importance of compliance and data ethics, especially in pharma.&#8221; Patient privacy and regulatory adherence aren&#8217;t constraints to be optimized around.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">His health equity example is the sharpest part of the conversation. A product performs well among patients with commercial insurance. AI identifies that group as most profitable and directs resources there. Populations with less access or lower adherence receive less attention \u2014 and the disparity widens, not through anyone&#8217;s decision, but through the system doing exactly what it was asked to do.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">&#8220;That&#8217;s why we need human judgment,&#8221; he emphasized. &#8220;AI can help us find opportunities that were hard to see before, but we must stay focused on delivering value across the entire patient population.&#8221;&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Personalization Starts With People<\/strong>&nbsp;<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">It&#8217;s hard to have a single recipe, but you&#8217;re touching on something essential. Too often when people talk about AI, they immediately think of software, data, and infrastructure \u2014 and forget about the human element.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">&#8220;That human piece is actually where personalization begins,&#8221; Alejandro said. His test is whether the system is designed around the people it serves \u2014 patients, HCPs, or the reps who have a few minutes with a physician and need what they bring into that room to be relevant.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">He frames it as more than strategic advantage: &#8220;It&#8217;s part of our moral clarity, and AI helps us simplify these decisions.&#8221; Everyone processes information differently, and AI can help simulate behavior and prepare field teams for those brief, high-stakes conversations.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Nataliya&#8217;s summary is worth keeping: &#8220;Personalization doesn&#8217;t mean creating a hundred versions of the same message. It means being smart about when and what we deliver to healthcare professionals.&#8221;&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>The Next Generation of Leaders<\/strong>&nbsp;<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Nataliya&#8217;s view is that future leaders will pair empathy with analytics \u2014 emotional intelligence and data fluency as a single competency rather than two.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Alejandro&#8217;s version emphasizes comfort with analytics, tools, and cross-functional work. Data literacy doesn&#8217;t mean expertise in everything; it means understanding what AI and advanced analytics can do and where they stop, well enough to ask the right questions.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Sometimes leaders are so focused on implementing their own strategy that they stop listening. Even if we disagree, it&#8217;s important to understand where others are coming from \u2014 and to have the courage to say, &#8216;You&#8217;re right.&#8217; Curiosity will be another defining trait. We may think AI has all the answers, but it still requires good judgment, understanding, and communication to drive a successful strategy.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Tomorrow&#8217;s leaders, in his framing, aren&#8217;t storytellers with data. They&#8217;re bridge builders \u2014 converting complexity into clarity and strategy into patient impact.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Nataliya named the specific problem they solve:&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The new leadership role is transformational. It&#8217;s like being a translator. The biggest blocker today is language \u2014 marketing talks about brand, analytics talks about models, and sales talks about stories. We need translators, people who can connect the dots across silos.&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Getting Functions to Work Together<\/strong>&nbsp;<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Alignment across analytics, marketing, sales, and market access takes time and trust, and most teams default to their own priorities and their own data. &#8220;The real power comes from connecting all those pieces into one story.&#8221;&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Each function has something to change. Marketing needs to move beyond measuring campaigns. Sales needs to look past short-term metrics. Analytics needs to translate rather than just produce. &#8220;Analytics should be the glue that connects these functions, and that glue is trust.&#8221;&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It&#8217;s not enough to launch a campaign or build a model. You need to know the goals, the objectives, and how results \u2014 whether through traditional analytics or AI \u2014 will actually impact the business. Sometimes, it means challenging business partners and asking tougher questions about what data is meant to answer.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Nataliya&#8217;s addition is that becoming data-driven is a culture problem more than a technology one. &#8220;You can hire the smartest data scientists and buy the best platforms, but if teams don&#8217;t understand the technology or its impact, the value will be limited.&#8221; Transformation happens when data stops being specialist property and becomes shared.&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Closing Thought<\/strong>&nbsp;<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Alejandro&#8217;s advice to teams: learn the business, not just the technology. &#8220;It&#8217;s easy to get caught up in the hype of AI tools, but the real value lies in connecting technology to business problems and empowering organizations.&#8221;&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That&#8217;s not solo work. &#8220;You can&#8217;t do it alone. You need to work with people who may not be familiar with the tech.&#8221; And it comes with a warning about which role to play: &#8220;Don&#8217;t be the person who only cares about numbers. Be the one who helps others get the most out of the technology.&#8221;&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">As generative tools, agents, and chatbots get easier to use, technical access stops being the differentiator. What&#8217;s left is the ability to connect data to the work people actually do.<\/p>\n<\/div><\/section>\n\n\n<section class=\"pt-related-episodes\" style=\"--pt-related-bg:#264cb8;color:#082480;--pt-related-title-color:#eff2ef;--pt-related-padding-top:50px;--pt-related-padding-bottom:60px;--pt-related-padding-x:0px\">\n            <div class=\"container\">\n                        <div class=\"pt-related-episodes__header\">\n                <h2 class=\"pt-related-episodes__title\">Our Latest Pharma Talk Episodes<\/h2>\n            <\/div>\n                <div class=\"pt-related-episodes__grid\">\n                                        <article class=\"pt-episode-card\">\n                    <a class=\"pt-episode-card__image\" href=\"https:\/\/pharma-talks.com\/episodes\/podcasts-medical-affairs-leadership\/\">\n                                                    <img width=\"371\" height=\"209\" 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11.3258 16.3021 10.8499 15.8747 10.6029L15.3744 11.4687L14.874 12.3345C14.9677 12.3886 14.9787 12.4133 14.9586 12.3878C14.9315 12.3532 14.8696 12.2512 14.8694 12.0965C14.8692 11.9454 14.928 11.8534 14.9423 11.8342C14.952 11.821 14.9295 11.8552 14.8288 11.9208L15.3744 12.7588ZM15.3744 11.4687L15.9673 10.6634L10.7966 6.85597L10.2037 7.66122L9.61072 8.46646L14.7814 12.2739L15.3744 11.4687ZM10.2037 7.66122L10.7388 6.81644C10.286 6.52965 9.64347 6.36117 9.03218 6.6466C8.36565 6.95781 8.10714 7.62689 8.11987 8.25032L9.11966 8.22991L10.1194 8.2095C10.1185 8.16275 10.1285 8.19137 10.0938 8.25775C10.0552 8.33159 9.98183 8.41046 9.87832 8.45879C9.67864 8.55202 9.5853 8.45326 9.66854 8.50599L10.2037 7.66122ZM9.11966 8.22991L8.11966 8.23281L8.14134 15.7119L9.14134 15.709L10.1413 15.7061L10.1197 8.22701L9.11966 8.22991ZM9.14134 15.709L8.14311 15.7684C8.17339 16.2771 8.35111 16.9731 9.00854 17.3242C9.65564 17.6698 10.3249 17.4421 10.7493 17.2072L10.2651 16.3323L9.78087 15.4573C9.69245 15.5063 9.66333 15.5057 9.68777 15.5024C9.72022 15.4979 9.82562 15.4933 9.95074 15.5601C10.0775 15.6278 10.1348 15.7209 10.1513 15.7559C10.1634 15.7818 10.146 15.758 10.1396 15.6496L9.14134 15.709ZM10.2651 16.3323L10.8382 17.1517L15.9475 13.5783L15.3744 12.7588L14.8012 11.9394L9.69195 15.5128L10.2651 16.3323Z\" fill=\"#EFF2EF\"\/><\/svg><span class=\"pt-episode-card__listen-text\">Listen Now!<\/span><\/a><\/div><\/div>                    <\/div>\n                <\/article>\n                                        <article class=\"pt-episode-card\">\n                    <a class=\"pt-episode-card__image\" href=\"https:\/\/pharma-talks.com\/episodes\/ai-in-pharma-communication\/\">\n                                                    <img width=\"371\" height=\"209\" src=\"https:\/\/pharma-talks.com\/wp-content\/uploads\/2026\/05\/Pharma-Talks-AI-and-Asia-What-Pharma-Marketers-Need-to-Hear-Right-Now-2-371x209.png\" class=\"attachment-pharmatalks-related-card size-pharmatalks-related-card\" alt=\"\" loading=\"lazy\" decoding=\"async\" sizes=\"auto, (max-width: 640px) 100vw, (max-width: 1024px) 50vw, 371px\" srcset=\"https:\/\/pharma-talks.com\/wp-content\/uploads\/2026\/05\/Pharma-Talks-AI-and-Asia-What-Pharma-Marketers-Need-to-Hear-Right-Now-2-371x209.png 371w, https:\/\/pharma-talks.com\/wp-content\/uploads\/2026\/05\/Pharma-Talks-AI-and-Asia-What-Pharma-Marketers-Need-to-Hear-Right-Now-2-300x169.png 300w, https:\/\/pharma-talks.com\/wp-content\/uploads\/2026\/05\/Pharma-Talks-AI-and-Asia-What-Pharma-Marketers-Need-to-Hear-Right-Now-2-1024x576.png 1024w, https:\/\/pharma-talks.com\/wp-content\/uploads\/2026\/05\/Pharma-Talks-AI-and-Asia-What-Pharma-Marketers-Need-to-Hear-Right-Now-2-768x432.png 768w, https:\/\/pharma-talks.com\/wp-content\/uploads\/2026\/05\/Pharma-Talks-AI-and-Asia-What-Pharma-Marketers-Need-to-Hear-Right-Now-2-1536x864.png 1536w, https:\/\/pharma-talks.com\/wp-content\/uploads\/2026\/05\/Pharma-Talks-AI-and-Asia-What-Pharma-Marketers-Need-to-Hear-Right-Now-2-2048x1152.png 2048w\" \/>                                            <\/a>\n                    <div class=\"pt-episode-card__body\">\n                        <p class=\"pt-episode-card__meta\">May 29, 2026<span class=\"pt-episode-card__duration\">12 min read<\/span><\/p>\n                        <h4 class=\"pt-episode-card__title\">\n                            <a href=\"https:\/\/pharma-talks.com\/episodes\/ai-in-pharma-communication\/\">Why Western Campaign Logic Breaks in Asian Markets\u00a0<\/a>\n                        <\/h4>\n                        <div class=\"pt-episode-card__detail\"><p class=\"pt-episode-card__guest-label\">Guest<\/p><p class=\"pt-episode-card__guest-name\">Gwenael Meneux, Bruno Senouci<\/p><div class=\"pt-episode-card__guest-meta\"><p class=\"pt-episode-card__guest-meta-position\">CO-CEO, CO-CEO<\/p><p class=\"pt-episode-card__guest-meta-company\">drcom<\/p><\/div><div class=\"pt-episode-card__actions\"><a class=\"pt-episode-card__listen\" href=\"https:\/\/pharma-talks.com\/episodes\/ai-in-pharma-communication\/\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"pt-episode-card__play-icon\" width=\"24\" height=\"24\" viewBox=\"0 0 24 24\" fill=\"none\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M15.3744 12.7588L14.8288 11.9208L14.8148 11.9298L14.8012 11.9394L15.3744 12.7588ZM15.3744 11.4687L14.7814 12.2739L14.826 12.3068L14.874 12.3345L15.3744 11.4687ZM10.2037 7.66122L10.7966 6.85597L10.7684 6.8352L10.7388 6.81644L10.2037 7.66122ZM9.11966 8.22991L10.1197 8.22701L10.1196 8.21826L10.1194 8.2095L9.11966 8.22991ZM9.14134 15.709L8.14134 15.7119L8.14142 15.7402L8.14311 15.7684L9.14134 15.709ZM10.2651 16.3323L10.7493 17.2072L10.7952 17.1818L10.8382 17.1517L10.2651 16.3323ZM12 21V20C7.58172 20 4 16.4183 4 12H3H2C2 17.5228 6.47715 22 12 22V21ZM21 12H20C20 16.4183 16.4183 20 12 20V21V22C17.5228 22 22 17.5228 22 12H21ZM12 3V4C16.4183 4 20 7.58172 20 12H21H22C22 6.47715 17.5228 2 12 2V3ZM12 3V2C6.47715 2 2 6.47715 2 12H3H4C4 7.58172 7.58172 4 12 4V3ZM15.3744 12.7588L15.9199 13.5969C16.3323 13.3285 16.8704 12.8393 16.8694 12.0938C16.8683 11.3258 16.3021 10.8499 15.8747 10.6029L15.3744 11.4687L14.874 12.3345C14.9677 12.3886 14.9787 12.4133 14.9586 12.3878C14.9315 12.3532 14.8696 12.2512 14.8694 12.0965C14.8692 11.9454 14.928 11.8534 14.9423 11.8342C14.952 11.821 14.9295 11.8552 14.8288 11.9208L15.3744 12.7588ZM15.3744 11.4687L15.9673 10.6634L10.7966 6.85597L10.2037 7.66122L9.61072 8.46646L14.7814 12.2739L15.3744 11.4687ZM10.2037 7.66122L10.7388 6.81644C10.286 6.52965 9.64347 6.36117 9.03218 6.6466C8.36565 6.95781 8.10714 7.62689 8.11987 8.25032L9.11966 8.22991L10.1194 8.2095C10.1185 8.16275 10.1285 8.19137 10.0938 8.25775C10.0552 8.33159 9.98183 8.41046 9.87832 8.45879C9.67864 8.55202 9.5853 8.45326 9.66854 8.50599L10.2037 7.66122ZM9.11966 8.22991L8.11966 8.23281L8.14134 15.7119L9.14134 15.709L10.1413 15.7061L10.1197 8.22701L9.11966 8.22991ZM9.14134 15.709L8.14311 15.7684C8.17339 16.2771 8.35111 16.9731 9.00854 17.3242C9.65564 17.6698 10.3249 17.4421 10.7493 17.2072L10.2651 16.3323L9.78087 15.4573C9.69245 15.5063 9.66333 15.5057 9.68777 15.5024C9.72022 15.4979 9.82562 15.4933 9.95074 15.5601C10.0775 15.6278 10.1348 15.7209 10.1513 15.7559C10.1634 15.7818 10.146 15.758 10.1396 15.6496L9.14134 15.709ZM10.2651 16.3323L10.8382 17.1517L15.9475 13.5783L15.3744 12.7588L14.8012 11.9394L9.69195 15.5128L10.2651 16.3323Z\" fill=\"#EFF2EF\"\/><\/svg><span class=\"pt-episode-card__listen-text\">Listen Now!<\/span><\/a><\/div><\/div>                    <\/div>\n                <\/article>\n                                        <article class=\"pt-episode-card\">\n                    <a class=\"pt-episode-card__image\" href=\"https:\/\/pharma-talks.com\/episodes\/future-of-pharma-content\/\">\n                                                    <img width=\"371\" height=\"209\" src=\"https:\/\/pharma-talks.com\/wp-content\/uploads\/2026\/05\/Pharma-Content-AI_-Whats-Next_-_-Pharma-Talks-1-371x209.png\" class=\"attachment-pharmatalks-related-card size-pharmatalks-related-card\" alt=\"\" loading=\"lazy\" decoding=\"async\" sizes=\"auto, (max-width: 640px) 100vw, (max-width: 1024px) 50vw, 371px\" srcset=\"https:\/\/pharma-talks.com\/wp-content\/uploads\/2026\/05\/Pharma-Content-AI_-Whats-Next_-_-Pharma-Talks-1-371x209.png 371w, https:\/\/pharma-talks.com\/wp-content\/uploads\/2026\/05\/Pharma-Content-AI_-Whats-Next_-_-Pharma-Talks-1-300x169.png 300w, https:\/\/pharma-talks.com\/wp-content\/uploads\/2026\/05\/Pharma-Content-AI_-Whats-Next_-_-Pharma-Talks-1-1024x576.png 1024w, https:\/\/pharma-talks.com\/wp-content\/uploads\/2026\/05\/Pharma-Content-AI_-Whats-Next_-_-Pharma-Talks-1-768x432.png 768w, https:\/\/pharma-talks.com\/wp-content\/uploads\/2026\/05\/Pharma-Content-AI_-Whats-Next_-_-Pharma-Talks-1-1536x864.png 1536w, https:\/\/pharma-talks.com\/wp-content\/uploads\/2026\/05\/Pharma-Content-AI_-Whats-Next_-_-Pharma-Talks-1-2048x1152.png 2048w\" \/>                                            <\/a>\n                    <div class=\"pt-episode-card__body\">\n                        <p class=\"pt-episode-card__meta\">May 21, 2026<span class=\"pt-episode-card__duration\">8 min read<\/span><\/p>\n                        <h4 class=\"pt-episode-card__title\">\n                            <a href=\"https:\/\/pharma-talks.com\/episodes\/future-of-pharma-content\/\">Relevance, Not Volume: Tim Pantello on Pharma Content\u00a0<\/a>\n                        <\/h4>\n                        <div class=\"pt-episode-card__detail\"><p class=\"pt-episode-card__guest-label\">Guest<\/p><p class=\"pt-episode-card__guest-name\">Tim Pantello<\/p><div class=\"pt-episode-card__guest-meta\"><p class=\"pt-episode-card__guest-meta-position\">Chief Executive Officer<\/p><p class=\"pt-episode-card__guest-meta-company\">Relevate Health<\/p><\/div><div class=\"pt-episode-card__actions\"><a class=\"pt-episode-card__listen\" href=\"https:\/\/pharma-talks.com\/episodes\/future-of-pharma-content\/\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"pt-episode-card__play-icon\" width=\"24\" height=\"24\" viewBox=\"0 0 24 24\" fill=\"none\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M15.3744 12.7588L14.8288 11.9208L14.8148 11.9298L14.8012 11.9394L15.3744 12.7588ZM15.3744 11.4687L14.7814 12.2739L14.826 12.3068L14.874 12.3345L15.3744 11.4687ZM10.2037 7.66122L10.7966 6.85597L10.7684 6.8352L10.7388 6.81644L10.2037 7.66122ZM9.11966 8.22991L10.1197 8.22701L10.1196 8.21826L10.1194 8.2095L9.11966 8.22991ZM9.14134 15.709L8.14134 15.7119L8.14142 15.7402L8.14311 15.7684L9.14134 15.709ZM10.2651 16.3323L10.7493 17.2072L10.7952 17.1818L10.8382 17.1517L10.2651 16.3323ZM12 21V20C7.58172 20 4 16.4183 4 12H3H2C2 17.5228 6.47715 22 12 22V21ZM21 12H20C20 16.4183 16.4183 20 12 20V21V22C17.5228 22 22 17.5228 22 12H21ZM12 3V4C16.4183 4 20 7.58172 20 12H21H22C22 6.47715 17.5228 2 12 2V3ZM12 3V2C6.47715 2 2 6.47715 2 12H3H4C4 7.58172 7.58172 4 12 4V3ZM15.3744 12.7588L15.9199 13.5969C16.3323 13.3285 16.8704 12.8393 16.8694 12.0938C16.8683 11.3258 16.3021 10.8499 15.8747 10.6029L15.3744 11.4687L14.874 12.3345C14.9677 12.3886 14.9787 12.4133 14.9586 12.3878C14.9315 12.3532 14.8696 12.2512 14.8694 12.0965C14.8692 11.9454 14.928 11.8534 14.9423 11.8342C14.952 11.821 14.9295 11.8552 14.8288 11.9208L15.3744 12.7588ZM15.3744 11.4687L15.9673 10.6634L10.7966 6.85597L10.2037 7.66122L9.61072 8.46646L14.7814 12.2739L15.3744 11.4687ZM10.2037 7.66122L10.7388 6.81644C10.286 6.52965 9.64347 6.36117 9.03218 6.6466C8.36565 6.95781 8.10714 7.62689 8.11987 8.25032L9.11966 8.22991L10.1194 8.2095C10.1185 8.16275 10.1285 8.19137 10.0938 8.25775C10.0552 8.33159 9.98183 8.41046 9.87832 8.45879C9.67864 8.55202 9.5853 8.45326 9.66854 8.50599L10.2037 7.66122ZM9.11966 8.22991L8.11966 8.23281L8.14134 15.7119L9.14134 15.709L10.1413 15.7061L10.1197 8.22701L9.11966 8.22991ZM9.14134 15.709L8.14311 15.7684C8.17339 16.2771 8.35111 16.9731 9.00854 17.3242C9.65564 17.6698 10.3249 17.4421 10.7493 17.2072L10.2651 16.3323L9.78087 15.4573C9.69245 15.5063 9.66333 15.5057 9.68777 15.5024C9.72022 15.4979 9.82562 15.4933 9.95074 15.5601C10.0775 15.6278 10.1348 15.7209 10.1513 15.7559C10.1634 15.7818 10.146 15.758 10.1396 15.6496L9.14134 15.709ZM10.2651 16.3323L10.8382 17.1517L15.9475 13.5783L15.3744 12.7588L14.8012 11.9394L9.69195 15.5128L10.2651 16.3323Z\" fill=\"#EFF2EF\"\/><\/svg><span class=\"pt-episode-card__listen-text\">Listen Now!<\/span><\/a><\/div><\/div>                    <\/div>\n                <\/article>\n                    <\/div>\n            <\/div>\n    <\/section>\n\n\n<style id=\"pharmatalks-content-split-style\">.pt-split__container.container{max-width:var(--pt-split-container-width,var(--container-width))}@media (width >= 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