{"id":10531,"date":"2024-04-24T07:46:26","date_gmt":"2024-04-24T11:46:26","guid":{"rendered":"https:\/\/ptp.cloud\/?p=10531"},"modified":"2025-06-23T23:33:25","modified_gmt":"2025-06-24T03:33:25","slug":"mastering-ai-architecture-life-sciences","status":"publish","type":"post","link":"https:\/\/ptp.cloud\/mastering-ai-architecture-life-sciences\/","title":{"rendered":"Mastering AI Architecture for Life Sciences: Balancing Top-Down and Bottom-Up Strategies"},"content":{"rendered":"[et_pb_section fb_built=&#8221;1&#8243; admin_label=&#8221;section&#8221; _builder_version=&#8221;4.16&#8243; custom_padding=&#8221;0px||0px|||&#8221; da_disable_devices=&#8221;off|off|off&#8221; global_colors_info=&#8221;{}&#8221; da_is_popup=&#8221;off&#8221; da_exit_intent=&#8221;off&#8221; da_has_close=&#8221;on&#8221; da_alt_close=&#8221;off&#8221; da_dark_close=&#8221;off&#8221; da_not_modal=&#8221;on&#8221; da_is_singular=&#8221;off&#8221; da_with_loader=&#8221;off&#8221; da_has_shadow=&#8221;on&#8221;][et_pb_row admin_label=&#8221;row&#8221; _builder_version=&#8221;4.25.0&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221; custom_padding=&#8221;||0px|||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.16&#8243; custom_padding=&#8221;|||&#8221; global_colors_info=&#8221;{}&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_text admin_label=&#8221;Text&#8221; _builder_version=&#8221;4.25.0&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221; custom_margin=&#8221;-14px|||||&#8221; custom_padding=&#8221;0px|||||&#8221; global_colors_info=&#8221;{}&#8221;]\n<p><iframe loading=\"lazy\" title=\"Mastering AI Architecture in Life Sciences\" width=\"1080\" height=\"608\" src=\"https:\/\/www.youtube.com\/embed\/iwQcWGyzPO8?feature=oembed\"  allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe><\/p>\n<p>&nbsp;<\/p>\n<h2 style=\"text-align: center;\"><em><a href=\"https:\/\/ptp.cloud\/the-rational-ai-architect-the-path-for-ai-in-life-sciences\/\">Access the full webinar here<\/a><\/em><\/h2>\n[\/et_pb_text][et_pb_divider _builder_version=&#8221;4.25.0&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;||-1px|||&#8221; global_colors_info=&#8221;{}&#8221;][\/et_pb_divider][et_pb_text content_tablet=&#8221;<\/p>\n<p><a href=%22https:\/\/aws.amazon.com\/marketplace\/seller-profile?id=40aef862-90e2-4a5f-9d98-2ef74b6cbf15%22><img class=%22wp-image-201 size-medium alignleft%22 src=%22https:\/\/ptp.cloud\/wp-content\/uploads\/2020\/07\/aws-seal-256x300.jpg%22 alt=%22%22 width=%22202%22 height=%22236%22 \/><\/a>PTP joined John Conway, Chief Visioneer Officer of <a href=%22https:\/\/www.20visioneers15.com\/%22>20\/15 Visioneers<\/a> to discuss the path for AI in Life Sciences. 2023 and 2024 have brought AI into almost every technology conversation. In most instances, the AI discussion is about \u201chow can we harness the value in the future\u201d. For drug discovery, most data environments will have to walk before they run.<\/p>\n<p>In this webinar PTP and 20\/15 Visioneers discussed:<\/p>\n<ul>\n<li>AI \u2013 the \u201cit\u201d word for 2024<\/li>\n<li>What is \u201cThe Rational AI Architect\u201d<\/li>\n<li>Best Practices for Early Stage Life Sciences data environments<\/li>\n<li>Case studies of PTP getting data \u201cready\u201d<\/li>\n<li>Roadmap for leveraging AI<\/li>\n<\/ul>\n<p><em><strong>Check out PTP&#8217;s CloudOps for Life Sciences<\/strong><\/em><\/p>\n<ul>\n<li style=%22list-style-type: none;%22>\n<ul>\n<li style=%22list-style-type: none;%22>\n<ul><\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li style=%22list-style-type: none;%22>\n<ul><\/ul>\n<\/li>\n<\/ul>\n<p>&#8221; content_phone=&#8221;<\/p>\n<p><a href=%22https:\/\/aws.amazon.com\/marketplace\/seller-profile?id=40aef862-90e2-4a5f-9d98-2ef74b6cbf15%22><img class=%22wp-image-201 size-medium alignleft%22 src=%22https:\/\/ptp.cloud\/wp-content\/uploads\/2020\/07\/aws-seal-256x300.jpg%22 alt=%22%22 width=%22161%22 height=%22188%22 \/><\/a>PTP joined John Conway, Chief Visioneer Officer of <a href=%22https:\/\/www.20visioneers15.com\/%22>20\/15 Visioneers<\/a> to discuss the path for AI in Life Sciences. 2023 and 2024 have brought AI into almost every technology conversation. In most instances, the AI discussion is about \u201chow can we harness the value in the future\u201d. For drug discovery, most data environments will have to walk before they run.<\/p>\n<p>In this webinar PTP and 20\/15 Visioneers discussed:<\/p>\n<ul>\n<li>AI \u2013 the \u201cit\u201d word for 2024<\/li>\n<li>What is \u201cThe Rational AI Architect\u201d<\/li>\n<li>Best Practices for Early Stage Life Sciences data environments<\/li>\n<li>Case studies of PTP getting data \u201cready\u201d<\/li>\n<li>Roadmap for leveraging AI<\/li>\n<\/ul>\n<p><em><strong>Check out PTP&#8217;s CloudOps for Life Sciences<\/strong><\/em><\/p>\n<ul>\n<li style=%22list-style-type: none;%22>\n<ul>\n<li style=%22list-style-type: none;%22>\n<ul><\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li style=%22list-style-type: none;%22>\n<ul><\/ul>\n<\/li>\n<\/ul>\n<p>&#8221; content_last_edited=&#8221;on|tablet&#8221; admin_label=&#8221;Text&#8221; _builder_version=&#8221;4.27.4&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221; custom_margin=&#8221;||-1px|||&#8221; global_colors_info=&#8221;{}&#8221;]\n<p><a href=\"https:\/\/aws.amazon.com\/marketplace\/seller-profile?id=40aef862-90e2-4a5f-9d98-2ef74b6cbf15\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-201 size-medium alignleft\" src=\"https:\/\/ptp.cloud\/wp-content\/uploads\/2020\/07\/aws-seal-256x300.jpg\" alt=\"\" width=\"150\" height=\"176\" \/><\/a><\/p>\n<p data-start=\"493\" data-end=\"1031\">Artificial Intelligence (AI) and Machine Learning (ML) are no longer future goals for life sciences\u2014they\u2019re current necessities. In this session, <a data-start=\"639\" data-end=\"664\" rel=\"noopener\" target=\"_new\" class=\"\" href=\"https:\/\/ptp.cloud\/\">PTP<\/a> joined John Conway, Chief Visioneer Officer of 20\/15 Visioneers, to discuss the practical realities of implementing AI in research environments. Titled <em data-start=\"817\" data-end=\"847\">\u201cThe Rational AI Architect,\u201d<\/em> this <a data-start=\"853\" data-end=\"930\" rel=\"noopener\" target=\"_new\" class=\"\" href=\"https:\/\/ptp.cloud\/events\/the-rational-ai-architect-at-bio-it-2024\/\">webinar<\/a> explores how biotech companies and research teams can lay the groundwork for successful AI projects.<\/p>\n<h3 data-start=\"1033\" data-end=\"1072\">The AI \u201cGold Rush\u201d in Life Sciences<\/h3>\n<p data-start=\"1074\" data-end=\"1535\">In 2023 and 2024, nearly every technology roadmap has been updated to include generative AI, LLMs, or predictive modeling. But for life sciences companies\u2014especially those still modernizing infrastructure\u2014AI can be more aspiration than reality. <a data-start=\"1319\" data-end=\"1395\" rel=\"noopener\" target=\"_new\" class=\"\" href=\"https:\/\/ptp.cloud\/services\/cloudops\/cloud-migration\/\">Cloud data migration<\/a> and governance must come first, and the foundation must be secure, scalable, and compliant with life sciences standards like GxP and HIPAA.<\/p>\n<p data-start=\"1537\" data-end=\"1899\">PTP\u2019s team has helped companies design for long-term success by aligning IT infrastructure for AI workloads, assessing readiness, and educating internal teams. This blog summarizes key takeaways from the conversation with John Conway and <a data-start=\"1775\" data-end=\"1867\" rel=\"noopener\" target=\"_new\" class=\"\" href=\"https:\/\/ptp.cloud\/developing-ai-and-ml-practices-insights-from-aaron-jeskey\/\">Aaron Jeskey<\/a>, Senior Cloud Architect at PTP.<\/p>\n<hr data-start=\"1901\" data-end=\"1904\" \/>\n<h3 data-start=\"1906\" data-end=\"1955\">Where AI Initiatives Begin\u2014and Why It Matters<\/h3>\n<p data-start=\"1957\" data-end=\"2046\">AI and ML requests in life sciences organizations typically originate in one of two ways:<\/p>\n<h4 data-start=\"2048\" data-end=\"2094\">Bottom-Up: From Researchers to Leadership<\/h4>\n<p data-start=\"2096\" data-end=\"2330\">Requests often come from bench scientists, data analysts, or bioinformaticians who see the potential of AI in their workflows. While technically promising, these initiatives struggle without organizational support. Challenges include:<\/p>\n<ul data-start=\"2332\" data-end=\"2498\">\n<li data-start=\"2332\" data-end=\"2364\">\n<p data-start=\"2334\" data-end=\"2364\">Lack of platform consistency<\/p>\n<\/li>\n<li data-start=\"2365\" data-end=\"2423\">\n<p data-start=\"2367\" data-end=\"2423\">Poorly defined processes for infrastructure management<\/p>\n<\/li>\n<li data-start=\"2424\" data-end=\"2465\">\n<p data-start=\"2426\" data-end=\"2465\">Limited buy-in from senior leadership<\/p>\n<\/li>\n<li data-start=\"2466\" data-end=\"2498\">\n<p data-start=\"2468\" data-end=\"2498\">Fragmented tools and shadow IT<\/p>\n<\/li>\n<\/ul>\n<p data-start=\"2500\" data-end=\"2609\">To scale successfully, research IT teams need alignment from leadership on governance, security, and funding.<\/p>\n<h4 data-start=\"2611\" data-end=\"2660\"><a href=\"https:\/\/www.linkedin.com\/in\/ajeskey\/\"><img loading=\"lazy\" decoding=\"async\" class=\"alignright\" src=\"https:\/\/ptp.cloud\/wp-content\/uploads\/2024\/04\/Aaron-Jeskey-leveraging-ai-in-life-sciences-the-rational-ai-architect-approach.jpg\" alt=\"Professional profile of Aaron Jeskey, Sr. Cloud Architect at PTP, with a brief summary of his career in AWS solutions and leadership roles.\" width=\"518\" height=\"291\" \/><\/a>Top-Down: From Leadership to Technical Teams<\/h4>\n<p data-start=\"2662\" data-end=\"2799\">When executives lead the charge for AI, expectations tend to be high\u2014but often misaligned with technical feasibility. Challenges include:<\/p>\n<ul data-start=\"2801\" data-end=\"3103\">\n<li data-start=\"2801\" data-end=\"2869\">\n<p data-start=\"2803\" data-end=\"2869\">A shortage of qualified cloud data engineers or DevOps resources<\/p>\n<\/li>\n<li data-start=\"2870\" data-end=\"2895\">\n<p data-start=\"2872\" data-end=\"2895\">Unrealistic timelines<\/p>\n<\/li>\n<li data-start=\"2896\" data-end=\"3065\">\n<p data-start=\"2898\" data-end=\"3065\">Missing foundational components (e.g., <a data-start=\"2937\" data-end=\"3030\" class=\"\" rel=\"noopener\" target=\"_new\" href=\"https:\/\/ptp.cloud\/data-orchestration-steps-to-success-in-life-sciences\/\">data orchestration<\/a>, monitoring, tagging strategies)<\/p>\n<\/li>\n<li data-start=\"3066\" data-end=\"3103\">\n<p data-start=\"3068\" data-end=\"3103\">Security and compliance blind spots<\/p>\n<\/li>\n<\/ul>\n<p data-start=\"3105\" data-end=\"3227\">Without sufficient technical resources or internal education, the disconnect between strategy and execution grows quickly.<\/p>\n<hr data-start=\"3229\" data-end=\"3232\" \/>\n<h3 data-start=\"3234\" data-end=\"3287\">Managing Expectations and Building Real Platforms<\/h3>\n<p data-start=\"3289\" data-end=\"3450\">Whether AI demand comes from the C-suite or the lab, the risks are similar: misalignment, wasted investment, and failed pilots. To mitigate this, PTP recommends:<\/p>\n<ul data-start=\"3452\" data-end=\"3872\">\n<li data-start=\"3452\" data-end=\"3593\">\n<p data-start=\"3454\" data-end=\"3593\">Starting with a <a data-start=\"3470\" data-end=\"3553\" rel=\"noopener\" target=\"_new\" class=\"\" href=\"https:\/\/ptp.cloud\/aws-well-architected-review\/\">Well-Architected Framework Review<\/a> to benchmark infrastructure readiness<\/p>\n<\/li>\n<li data-start=\"3594\" data-end=\"3650\">\n<p data-start=\"3596\" data-end=\"3650\">Implementing cloud governance and cost control early<\/p>\n<\/li>\n<li data-start=\"3651\" data-end=\"3800\">\n<p data-start=\"3653\" data-end=\"3800\">Leveraging scalable platforms like <a data-start=\"3688\" data-end=\"3768\" class=\"\" rel=\"noopener\" target=\"_new\" href=\"https:\/\/ptp.cloud\/aws-consulting\/aws-for-life-sciences\/\">AWS for Life Sciences<\/a> to support evolving workloads<\/p>\n<\/li>\n<li data-start=\"3801\" data-end=\"3872\">\n<p data-start=\"3803\" data-end=\"3872\">Building internal fluency through education and transparent reporting<\/p>\n<\/li>\n<\/ul>\n<p data-start=\"3874\" data-end=\"4181\">In one PTP case study, a genomics company attempted to implement ML without a centralized data repository. After a platform redesign and <a data-start=\"4011\" data-end=\"4094\" class=\"\" rel=\"noopener\" target=\"_new\" href=\"https:\/\/ptp.cloud\/services\/cloudops\/cloud-engineering\/\">cloud engineering support<\/a>, they reduced duplication, improved compliance, and accelerated model training by 30%.<\/p>\n<hr data-start=\"4183\" data-end=\"4186\" \/>\n<h3 data-start=\"4188\" data-end=\"4252\">Conclusion: Rational AI Starts with Realistic Infrastructure<\/h3>\n<p data-start=\"4254\" data-end=\"4525\">Whether requests come top-down or bottom-up, life sciences companies need a unified strategy for implementing AI. That means prioritizing foundational architecture, building in compliance from day one, and maintaining strong communication between research and leadership.<\/p>\n<p data-start=\"4527\" data-end=\"4822\">PTP helps clients develop cloud-native AI platforms that are secure, scalable, and optimized for scientific research. From <a data-start=\"4650\" data-end=\"4726\" class=\"\" rel=\"noopener\" target=\"_new\" href=\"https:\/\/ptp.cloud\/managed-services-for-life-sciences\/\">managed IT for labs<\/a> to multi-region HPC clusters, we help life sciences companies move from AI talk to AI outcomes.<\/p>\n[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=&#8221;1_3,1_3,1_3&#8243; _builder_version=&#8221;4.27.4&#8243; _module_preset=&#8221;default&#8221; background_color=&#8221;#f2f2f2&#8243; custom_margin=&#8221;27px|auto||auto||&#8221; custom_padding=&#8221;18px|18px|18px|18px|true|true&#8221; border_radii=&#8221;on|5px|5px|5px|5px&#8221; locked=&#8221;off&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;1_3&#8243; _builder_version=&#8221;4.27.4&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][\/et_pb_column][et_pb_column type=&#8221;1_3&#8243; _builder_version=&#8221;4.27.4&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_image src=&#8221;https:\/\/ptp.cloud\/wp-content\/uploads\/2024\/03\/Scientific-Data-Management-Best-Practices-to-Achieve-RD-Operational-Excellence.jpg&#8221; align_tablet=&#8221;center&#8221; align_phone=&#8221;center&#8221; align_last_edited=&#8221;on|tablet&#8221; _builder_version=&#8221;4.25.1&#8243; _module_preset=&#8221;default&#8221; max_width=&#8221;100%&#8221; max_width_tablet=&#8221;51%&#8221; max_width_phone=&#8221;86%&#8221; max_width_last_edited=&#8221;on|desktop&#8221; module_alignment_tablet=&#8221;center&#8221; module_alignment_phone=&#8221;center&#8221; module_alignment_last_edited=&#8221;on|tablet&#8221; global_colors_info=&#8221;{}&#8221;][\/et_pb_image][et_pb_text _builder_version=&#8221;4.27.4&#8243; _module_preset=&#8221;default&#8221; module_alignment=&#8221;center&#8221; custom_padding=&#8221;|0px||0px|false|true&#8221; custom_padding_tablet=&#8221;|146px||146px|false|true&#8221; custom_padding_phone=&#8221;|50px||50px|false|true&#8221; custom_padding_last_edited=&#8221;on|tablet&#8221; global_colors_info=&#8221;{}&#8221;]\n<p style=\"text-align: center;\"><em><strong>Download our white paper on<\/strong><\/em><em><strong><a href=\"https:\/\/ptp.cloud\/scientific-data-management-best-practices-to-achieve-rd-operational-excellence\/\"> Scientific Data Management: Best Practices to Achieve R&amp;D Operational Excellence<\/a><\/strong><\/em><\/p>\n[\/et_pb_text][\/et_pb_column][et_pb_column type=&#8221;1_3&#8243; _builder_version=&#8221;4.27.4&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][\/et_pb_column][\/et_pb_row][\/et_pb_section]\n<span class=\"et_bloom_bottom_trigger\"><\/span>","protected":false},"excerpt":{"rendered":"<p>Discover the key aspects of mastering AI architecture in the life sciences industry with expert insights from Aaron Jeskey, Senior Cloud Architect at PTP. This blog post explores the innovative approaches and strategies used to leverage AI for scientific advancements. <\/p>\n","protected":false},"author":2,"featured_media":10587,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"PTP joined John Conway of 20\/15 Visioneers to discuss the path for AI in Life Sciences. 2023 and 2024 have brought AI into almost every technology conversation. In most instances, the AI discussion is about \u201chow can we harness the value in the future\u201d. For drug discovery, most data environments will have to walk before they run.\r\nIn this webinar PTP and 20\/15 Visioneers discussed:\r\n<ul>\r\n \t<li>AI \u2013 the \u201cit\u201d word for 2024<\/li>\r\n \t<li>What is \u201cThe Rational AI Architect\u201d<\/li>\r\n \t<li>Best Practices for Early Stage Life Sciences data environments<\/li>\r\n \t<li>Case studies of PTP getting data \u201cready\u201d<\/li>\r\n \t<li>Roadmap for leveraging AI<\/li>\r\n<\/ul>\r\n\u00a0\r\n\r\n<strong>Speakers<\/strong>\r\n<a href=\"https:\/\/www.linkedin.com\/in\/john-f-conway-678b2a3\/\">John Conway<\/a> - Chief Visioneer Officer, 20\/15 Visioneers\r\n<a href=\"https:\/\/www.linkedin.com\/in\/ajeskey\/\">Aaron Jeskey<\/a> - Sr. Cloud Architect, PTP\r\n\r\n\u00a0\r\n\r\n[embed]https:\/\/youtu.be\/iwQcWGyzPO8[\/embed]\r\n\r\n\u00a0\r\n<h3><a href=\"https:\/\/ptp.cloud\/aws-consulting\/aws-for-life-sciences\/\">Check out PTP's ClouOps for Life Sciences!<\/a><\/h3>","_et_gb_content_width":"","content-type":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[12,9,180,83,15],"tags":[],"table_tags":[],"class_list":["post-10531","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-aws-for-life-sciences-archive","category-cloudops-archive","category-devops-archive","category-learning-videos-archive","category-webinars-archive"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.1.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Building a Rational AI Strategy in Life Sciences | PTP<\/title>\n<meta name=\"description\" content=\"Uncover challenges and best practices for implementing AI and ML in early-stage life sciences environments.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/ptp.cloud\/mastering-ai-architecture-life-sciences\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Building a Rational AI Strategy in Life Sciences | PTP\" \/>\n<meta property=\"og:description\" content=\"Uncover challenges and best practices for implementing AI and ML in early-stage life sciences environments.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/ptp.cloud\/mastering-ai-architecture-life-sciences\/\" \/>\n<meta property=\"og:site_name\" content=\"PTP | Cloud Experts | Biotech Enablers\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/PTPCloud\" \/>\n<meta property=\"article:published_time\" content=\"2024-04-24T11:46:26+00:00\" \/>\n<meta property=\"article:modified_time\" 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