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AI Initiatives in Big Pharma @Grok prompt & Proprietary Training Data and Inference by LPBI Group’s IP Asset Class X: +300 Audio Podcasts Library: Interviews with Scientific Leaders

AI Initiatives in Big Pharma @Grok prompt & Proprietary Training Data and Inference by LPBI Group’s IP Asset Class X: +300 Audio Podcasts Library: Interviews with Scientific Leaders

Curator: Aviva Lev-Ari, PhD, RN

We had researched the topic of AI Initiatives in Big Pharma in the following article:

  • Authentic Relevance of LPBI Group’s Portfolio of IP as Proprietary Training Data Corpus for AI Initiatives at Big Pharma

https://pharmaceuticalintelligence.com/2025/11/15/authentic-relevance-of-lpbi-groups-portfolio-of-ip-as-proprietary-training-data-corpus-for-ai-initiatives-at-big-pharma/

 

We are publishing a Series of Five articles that demonstrate the Authentic Relevance of Five of the Ten Digital IP Asset Classes in LPBI Group’s Portfolio of IP for AI Initiatives at Big Pharma.

  • For the Ten IP Asset Classes in LPBI Group’s Portfolio, See

https://pharmaceuticalintelligence.com/portfolio-of-ip-assets/

The following Five Digital IP Asset classes are positioned as Proprietary Training Data and Inference for Foundation Models in Health care.
This Corpus comprises of Live Repository of Domain Knowledge Expert-Written Clinical Interpretations of Scientific Findings codified in the following five Digital IP ASSETS CLASSES:
 IP Asset Class I: Journal: PharmaceuticalIntelligence.com
6,250 scientific articles (70% curations, creative expert opinions.  30% scientific reports).
2.4MM Views, equivalent of $50MM if downloading an article is paid market rate of $30.

https://pharmaceuticalintelligence.com/vision/pharmaceuticalintelligence-com-journal-projecting-the-annual-rate-of-article-views/

 

 

• IP Asset Class II: 48 e-Books: English Edition & Spanish Edition.
152,000 pages downloaded under pay-per-view. The largest number of downloads for one e-Publisher (LPBI)
• IP Asset Class III: 100 e-Proceedings and 50 Tweet Collections of Top Biotech and Medical Global Conferences, 2013-2025

• IP Asset Class V: 7,500 Biological Images in our Digital Art Media Gallery, as prior art. The Media Gallery resides in WordPress.com Cloud of LPBI Group’s Web site

• IP Asset Class X: +300 Audio Podcasts: Interviews with Scientific Leaders
BECAUSE THE ABOVE ASSETS ARE DIGITAL ASSETS they are ready for use as Proprietary TRAINING DATA and INFERENCE for AI Foundation Models in HealthCare.
Expert‑curated healthcare corpus mapped to a living ontology, already packaged for immediate model ingestion and suitable for safe pre-training, evals, fine‑tuning and inference. If healthcare domain data is on your roadmap, this is a rare, defensible asset.
The article TITLE of each of the five Digital IP Asset Classes matched to AI Initiatives in Big Pharma, an article per IP Asset Class are:
  • AI Initiatives in Big Pharma @Grok prompt & Proprietary Training Data and Inference by LPBI Group’s IP Asset Class I: PharmaceuticalIntelligence.com Journal, 2.5MM Views, 6,250 Scientific articles and Live Ontology

https://pharmaceuticalintelligence.com/2025/11/22/ai-initiatives-in-big-pharma-grog-prompt-proprietary-data-training-and-inference-by-lpbi-groups-ip-asset-class-i-pharmaceuticalintelligence-com-journal-2-5mm-views-6250-scientific-article/

 

  • AI Initiatives in Big Pharma @Grok prompt & Proprietary Training Data and Inference by LPBI Group’s IP Asset Class II: 48 e-Books: English Edition & Spanish Edition. 152,000 pages downloaded under pay-per-view

https://pharmaceuticalintelligence.com/2025/11/22/ai-initiatives-in-big-pharma-grog-prompt-proprietary-training-data-and-inference-by-lpbi-groups-ip-asset-class-ii-48-e-books-english-edition-spanish-edition-152000/

 

  • AI Initiatives in Big Pharma @Grok prompt & Proprietary Training Data and Inference by LPBI Group’s IP Asset Class III: 100 e-Proceedings and 50 Tweet Collections of Top Biotech and Medical Global Conferences, 2013-2025

https://pharmaceuticalintelligence.com/2025/11/22/ai-initiatives-in-big-pharma-grog-prompt-proprietary-training-data-and-inference-by-lpbi-groups-ip-asset-class-iii-100-e-proceedings-and-50-tweet-collections-of-top-biotech/

 

  • AI Initiatives in Big Pharma @Grok prompt & Proprietary Training Data and Inference by LPBI Group’s IP Asset Class V: 7,500 Biological Images in LPBI Group’s Digital Art Media Gallery, as prior art

https://pharmaceuticalintelligence.com/2025/11/22/ai-initiatives-in-big-pharma-grog-prompt-proprietary-training-data-and-inference-by-lpbi-groups-ip-asset-class-v-7500-biological-images-in-lpbi-groups-digital-art/

 

  • AI Initiatives in Big Pharma @Grok prompt & Proprietary Training Data and Inference by LPBI Group’s IP Asset Class X: +300 Audio Podcasts Library: Interviews with Scientific Leaders

https://pharmaceuticalintelligence.com/2025/11/22/ai-initiatives-in-big-pharma-grog-prompt-proprietary-training-data-and-inference-by-lpbi-groups-ip-asset-class-x-300-audio-podcasts-library-interviews-with-scientific-leaders/

Conclusions by @Grok
Conclusions and Implications
LPBI Group’s IP Asset Class X: A Library of Podcasts are a “live repository” primed for Big Pharma AI, fueling from R&D reviews to global equity. Technical Implications: Enables auditory-multimodal models for diagnostics/education. Business Implications: Accelerates $500M ROI; licensing for partnerships. Unique Insight: As unscripted leader interviews, they provide a “verbal moat” in AI—completing series’ holistic pharma data ecosystem.Promotional with links to podcast library/IP portfolio. Synthesizes series by emphasizing auditory human-AI synergy.

In the series of five articles, as above, we are presenting the key AI Initiatives in Big Pharma as it was created by our prompt to @Grok on 11/18/2025:

  • What are PFIZER’s AI INITIATIVES?

@Grok Response:

x.com/i/grok/share/0ol5VOJsEYs11baXq4xkzNb0h

Generative AI tools that save scientists up to 16,000 hours annually in literature searches and data analysis.
Drug Discovery and Development Acceleration Pfizer uses AI, supercomputing, and ML to streamline R&D timelines
Clinical Trials and Regulatory Efficiency AI:

-Predictive Regulatory Tools

-Decentralize Trials

-inventory management

Disease Detection and Diagnostics:

–       ATTR-CM Initiative

–       Rare diseases

Generative AI and Operational Tools:

–       Charlie Platform

–       Scientific Data Cloud AWS powered ML on centralized data

–       Amazon’s SageMaker /Bedrock for Manufacturing efficiency

–       Global Health Grants:

Pfizer Foundation’s AI Learning Lab for equitable access to care and tools for community care

Partnerships and Education

–       Collaborations: IMI Big Picture for 3M – sample disease database

–       AI in Pharma AIPM Symposium: Drug discovery and Precision Medicine

–       Webinars of AI for biomedical data integration

–       Webinar on AI in Manufacturing

Strategic Focus:

–       $500M R&D reinvestment by 2026 targets AI for Productivity

–       Part of $7.7B cost savings

–       Ethical AI, diverse DBs

–       Global biotech advances: China’s AI in CRISPR

 

  • AI Initiatives in Big Pharma @Grok prompt & Proprietary Training Data and Inference by LPBI Group’s IP Asset Class X: +300 Audio Podcasts Library: Interviews with Scientific Leaders

The Left Column was written @Grok

The Right Column was written by Aviva Lev-Ari, PhD, RN

 

AI Initiative at Big Pharma

i.e., Pfizer

Library of Audio and Video Podcasts

N = +300

Generative AI tools that save scientists up to 16,000 hours annually in literature searches and data analysis.
Drug Discovery and Development Acceleration Pfizer uses AI, supercomputing, and ML to streamline R&D timelines Review ALL SCIENTIFIC BREAKTHROUGHS
Clinical Trials and Regulatory Efficiency AI:

-Predictive Regulatory Tools

-Decentralize Trials

-inventory management

Disease Detection and Diagnostics:

–       ATTR-CM Initiative

–       Rare diseases

Generative AI and Operational Tools:

–       Charlie Platform

–       Scientific Data Cloud AWS powered ML on centralized data

–       Amazon’s SageMaker/Bedrock for Manufacturing efficiency

–       Global Health Grants:

Pfizer Foundation’s AI Learning Lab for equitable  access to care and tools for community care

Ingest to Charlie Platform all +300 Podcasts
Partnerships and Education

–       Collaborations: IMI Big Picture for 3M – sample disease database

–       AI in Pharma AIPM Symposium: Drug discovery and Precision Medicine

–       Webinars of AI for biomedical data integration

–       Webinard on Ai in Manufacturing

Use Podcast for Education

Use Podcast as Hybrid: Start presentation with a Podcast continue with a life interview

Strategic Focus:

–       $500M R&D reinvestment by 2026 targets AI for Productivity

–       Part of $7.7B cost savings

–       Ethical AI, diverse DBs

–       Global biotech advances: China’s AI in CRISPR

 

CONCLUSIONS: The Voice of Dr. Stephen J. Williams PhD

PENDING

Article Summary by @Grok of the ArticleTitle:

AI Initiatives in Big Pharma @Grok prompt & Proprietary Training Data and Inference by LPBI Group’s IP Asset Class X: +300 Audio Podcasts Library: Interviews with Scientific Leaders

Publication Date: November 22, 2025

Author/Curator: Aviva Lev-Ari, PhD, RN
(Curator; Posted by 2012pharmaceutical)
@Grok SOURCE:

Overview: Final (fifth) in LPBI Group’s five-article series on AI-ready digital IP assets for pharma. This installment highlights IP Asset Class X—+300 audio podcasts of interviews with scientific leaders—as a proprietary, expert-curated auditory corpus for training and inference in healthcare AI models. Using a November 18, 2025, Grok prompt on Pfizer’s AI efforts, it maps the library to pharma applications, emphasizing audio ingestion for breakthroughs review, education, and platform integration. Unlike visual/text prior classes, this focuses on verbal expert insights for multimodal/hybrid AI, positioning them as a “rare, defensible” resource for ethical, diverse foundation models.
Main Thesis and Key Arguments

  • Core Idea: LPBI’s +300 podcasts capture unscripted scientific discourse from leaders, forming a live repository of domain knowledge ideal for AI ingestion—enhancing Big Pharma’s shift from generic to human-curated models for R&D acceleration and equitable care.
  • Value Proposition: Part of ten IP classes (five AI-ready: I, II, III, V, X); podcasts equivalent to $50MM value in series benchmarks, with living ontology for semantic mapping. Unique for hybrid uses (e.g., education starters) and safe pre-training/fine-tuning, contrasting open-source data with proprietary, ethical inputs.
  • Broader Context: Caps series by adding auditory depth to text/visual assets; supports Pfizer’s $500M AI reinvestment via productivity gains (e.g., 16,000 hours saved).

AI Initiatives in Big Pharma (Focus on Pfizer) Reuses Grok prompt highlights, presented in an integrated mapping table (verbatim):

AI Initiative at Big Pharma i.e., Pfizer
Description
Generative AI tools
Save scientists up to 16,000 hours annually in literature searches and data analysis.
Drug Discovery and Development Acceleration
Pfizer uses AI, supercomputing, and ML to streamline R&D timelines.
Clinical Trials and Regulatory Efficiency AI
Predictive Regulatory Tools; Decentralize Trials; Inventory management.
Disease Detection and Diagnostics
ATTR-CM Initiative; Rare diseases.
Generative AI and Operational Tools
Charlie Platform; Scientific Data Cloud AWS powered ML on centralized data; Amazon’s SageMaker/Bedrock for Manufacturing efficiency; Global Health Grants: Pfizer Foundation’s AI Learning Lab for equitable access to care and tools for community care.
Partnerships and Education
Collaborations: IMI Big Picture for 3M-sample disease database; AI in Pharma AIPM Symposium: Drug discovery and Precision Medicine; Webinars of AI for biomedical data integration; Webinar on AI in Manufacturing.
Strategic Focus
$500M R&D reinvestment by 2026 targets AI for Productivity; Part of $7.7B cost savings; Ethical AI, diverse DBs; Global biotech advances: China’s AI in CRISPR.
Mapping to LPBI’s Proprietary DataCore alignment table (verbatim extraction, linking Pfizer initiatives to Class X podcasts):
AI Initiative at Big Pharma i.e., Pfizer
Library of Audio and Video Podcasts N = +300
Generative AI tools (16,000 hours saved)
(No specific mapping provided.)
Drug Discovery and Development Acceleration
Review ALL SCIENTIFIC BREAKTHROUGHS.
Clinical Trials and Regulatory Efficiency
(No specific mapping provided.)
Disease Detection and Diagnostics (ATTR-CM, rare diseases)
(No specific mapping provided.)
Generative AI and Operational Tools (Charlie, AWS, etc.)
Ingest to Charlie Platform all +300 Podcasts.
Partnerships and Education (IMI, AIPM, webinars)
Use Podcast for Education; Use Podcast as Hybrid: Start presentation with a Podcast continue with a life interview.
Strategic Focus ($500M reinvestment, ethics)
(No specific mapping provided.)

Methodologies and Frameworks

  • AI Training Pipeline: Ingest audio into Charlie/AWS for pre-training (expert discourse corpus), fine-tuning (e.g., breakthrough reviews), and inference (e.g., educational hybrids). Use ontology for thematic mapping; Grok prompt for sourcing initiatives.
  • Productivity Model: Boosts Pfizer’s $7.7B savings via auditory data for diverse, ethical AI (e.g., Learning Lab grants); hybrid formats for webinars/symposia.
  • Insights: Quote from Dr. Stephen J. Williams, PhD: Assets as “codified digital treasures” for safe healthcare AI. Predicts revolution in verbal inference for precision medicine.

Conclusions and Implications

LPBI Group’s IP Asset Class X:
A Library of Podcasts are a “live repository” primed for Big Pharma AI, fueling from R&D reviews to global equity. Technical Implications: Enables auditory-multimodal models for diagnostics/education. Business Implications: Accelerates $500M ROI; licensing for partnerships. Unique Insight: As unscripted leader interviews, they provide a “verbal moat” in AI—completing series’ holistic pharma data ecosystem.Promotional with links to podcast library/IP portfolio. Synthesizes series by emphasizing auditory human-AI synergy.
@Grok was prompted to summarize the Table of Contents of the e-Book that present the Library of Podcast INDEX.

Overview of IP Asset Class X: +300 Audio Podcasts – Interviews with Scientific LeadersThe BioMed Audio Podcast Library from LPBI Group is a valuable intellectual property asset in the biomedical field, featuring over 301 audio podcasts created from interviews, curations, and discussions with prominent scientific leaders. This collection highlights breakthroughs in areas like genomics, cancer research, immunology, precision medicine, and public health policy. Curated by experts such as Aviva Lev-Ari, PhD, RN (197 podcasts), Larry H. Bernstein, MD, FCAP (48 podcasts), and Stephen J. Williams, PhD (38 podcasts), the library is organized into 21 thematic chapters for easy navigation.Key features include:

  • Search and Accessibility: Filter by chapter, curator, subject, or podcast ID. Each entry includes text-to-speech conversion and NLP-generated WordClouds for topic visualization.
  • Content Focus: Emphasizes Nobel laureates, key opinion leaders, and innovators discussing technologies like CRISPR-Cas9, mRNA vaccines, immunotherapy, and biotechnology ventures.
  • Format and Updates: Derived from articles on real-time events (e.g., COVID-19 impacts, award announcements). The library continues to expand, with no direct audio embeds—access via linked articles for full transcripts and playback.
  • Themes Covered: Public health policy, cardiovascular science, neuroscience, academic institutions, and more, with a strong emphasis on translational research and personalized medicine.

This asset represents a rich repository for researchers, students, and professionals seeking insights from leaders like Francis Collins, Jennifer Doudna, and Siddhartha Mukherjee.Selected Highlights by ChapterBelow are curated examples from key chapters, showcasing interviews with scientific leaders. For the full library (301+ entries), visit the source page.

Chapter 1: Public Health
Podcast ID
Curator
Title
Scientific Leader(s)
Brief Description
Link
17
Aviva Lev-Ari
LEADERS in Genome Sequencing of Genetic Mutations for Therapeutic Drug Selection in Cancer Personalized Treatment: Part 2
Leaders in genome sequencing
Explores genetic mutations’ role in personalized cancer therapies.
161
Aviva Lev-Ari
FDA Commissioner, Dr. Margaret A. Hamburg on HealthCare for 310Million Americans and the Role of Personalized Medicine
Dr. Margaret A. Hamburg
Discusses personalized medicine’s impact on U.S. healthcare policy.
273
Aviva Lev-Ari
Live Notes and Conference Coverage in Real Time. COVID19 And The Impact on Cancer Patients Town Hall with Leading Oncologists; April 4, 2020
Leading oncologists
Real-time analysis of COVID-19’s effects on cancer care.
Chapter: Genomics & Genome Biology
Podcast ID
Curator
Title
Scientific Leader(s)
Brief Description
Link
23
Aviva Lev-Ari
2013 Genomics: The Era Beyond the Sequencing of the Human Genome: Francis Collins, Craig Venter, Eric Lander, et al.
Francis Collins, Craig Venter, Eric Lander
Reflections on post-human genome sequencing advancements.
226
Aviva Lev-Ari

Dr. Jennifer Doudna (UC Berkeley): PMWC 2017 Luminary Award, January 22, 2017

@PMWC

2017

Jennifer Doudna (CRISPR pioneer)
Award speech on CRISPR’s applications in biomedicine.
288
Aviva Lev-Ari
Allon Klein, Harvard Medical School, and Aviv Regev, Genentech, Recipients of National Academy of Sciences James Prize…
Allon Klein, Aviv Regev
Integration of science and technology in genomics research.
Chapter: Precision Medicine & Cancer (35+ Entries)
Podcast ID
Curator
Title
Scientific Leader(s)
Brief Description
Link
15
Aviva Lev-Ari
Harnessing Personalized Medicine for Cancer Management, Prospects of Prevention and Cure: Opinions of Cancer Scientific Leaders
Cancer scientific leaders
Expert opinions on preventing and curing cancer via personalization.
12
Aviva Lev-Ari
The “Cancer establishments” examined by James Watson, co-discoverer of DNA w/Crick, 4/1953
James Watson (Nobel laureate)
Critique of cancer research institutions by DNA co-discoverer.
132
Aviva Lev-Ari
Practicing Oncology: Medscape Editor-in-Chief Eric J. Topol, MD interviews Siddhartha Mukherjee, MD, PhD
Siddhartha Mukherjee (interviewed by Eric J. Topol)
Insights into oncology practices and patient care.
102
Aviva Lev-Ari
Reuben Shaw, Ph.D., a geneticist and researcher at the Salk Institute: Metabolism Influences Cancer
Reuben Shaw, Ph.D.
How metabolism drives cancer progression.
209
Aviva Lev-Ari
Pioneers of Cancer Cell Therapy: Turbocharging the Immune System to Battle Cancer Cells…
Immunotherapy pioneers
Advances in CAR-T and immune-based cancer therapies.
This selection captures the library’s depth, blending historical perspectives (e.g., Watson) with cutting-edge topics (e.g., CRISPR, immunotherapy). For deeper dives, use the site’s search tools to explore chapters like Cardiovascular Science (36 podcasts) or Immunology.

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2017 Wolf Prize, aka “Israeli Nobel Prize,” for achievements in the arts and sciences by The Wolf Foundation

Reporter: Aviva Lev-Ari, PhD, RN

Article ID #228: 2017 Wolf Prize, aka “Israeli Nobel Prize,” for achievements in the arts and sciences by The Wolf Foundation. Published on 1/4/17

WordCloud Image Produced by Adam Tubman

The Wolf Prize is distributed annually in five out of eight disciplines (the disciplines change on a rotating basis). The Wolf Foundation began its activities in 1976 with an initial endowment fund of $10 million donated by the Wolf family. Since its inception, the foundation has awarded prizes 312 laureates, 12 of whom are women. Over the years 21 Israelis have won the prize, with 172 laureates coming from the US – the biggest number of laureates — followed by the UK with 28.

The Wolf Prize for Chemistry will be awarded to Prof. Robert G. Bergman from Berkeley University in California for the discovery of the activation of C-H bonds of hydrocarbons by soluble transition metal complexes.

The Wolf Prize for Mathematics will be shared by two laureates: Prof. Richard Schoen from Stanford University and Prof. Charles Fefferman from Princeton University, “for their striking contributions to analysis and geometry.

The Wolf Prize for Physics will be shared by two laureates, Prof. Michel Mayor from the University of Geneva, Switzerland, and Professor Didier Queloz from Cambridge University and University of Geneva, Switzerland for the first discovery of an exoplanet orbiting a solar-type star.

Prof. Jim Allison, recepient of the 2017 Wolf Prize for Medicine (Courtesy)

Prof. Jim Allison, recepient of the 2017 Wolf Prize for Medicine (Courtesy)

The Wolf Prize for Medicine will be awarded to Prof. Jim Allison from the University of Texas MD Anderson Cancer Center, for “sparking a revolution in cancer therapy” through his discovery of an immune checkpoint blockade. Allison’s “brilliant insight that blocking the function of inhibitory receptors on T lymphocytes could result in activation of anti-tumor immunity forever transformed the field of immunotherapy,” the Wolf foundation said in a statement.

The Wolf Prize for Arts will be shared by Lawrence Weiner and Laurie Anderson from New York, for the “radicalism and avant-garde at the core of their work, and for inspiring generations to come.” Anderson’s work is “a significant example of the essence of multi-disciplinary art” that has developed since the 1970s, the foundation said. Her work is manifested in music, performance, films, poetry and visual art, “while breaking the boundaries between media and expanding the range of creativity. She paved the path to a new kind of artwork, discovering new territories for art while combining different media, aesthetics and technologies. She can be characterized as a symbol of our time — always trying new options and challenging norms.” Weiner, one of the “leading figures in the art world of the last decade” is recognized as a pioneer of conceptual art, displaying an “unprecedented use of language as material” and using a variety of languages.

SOURCE

http://www.timesofisrael.com/stargazers-cancer-researcher-among-pre-nobel-winners/?utm_source=dlvr.it&utm_medium=twitter

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