Leaders in Pharmaceutical Business Intelligence Group, LLC, Doing Business As LPBI Group, Newton, MA

Drug Development Process been Revolutionized by Artificial Intelligence (AI) Technologies

Curators: Stephen J. Williams, PhD and Aviva Lev-Ari, PhD, RN

The Voice of Stephen J. Williams, PhD

LPBI Group, CSO

PENDING

The Voice of Aviva Lev-Ari, PhD, RN

1.0 LPBI Group and 2.0 LPBI Group, Founder

With the advent of AI in the last 5-7 years in our fields: Pharmaceutical, Life Sciences and Medicine, LPBI Group had launched several initiatives to advance the frontier of knowledge by using our own contents repositories of +8 giga bytes for experimenting with Machine Learning (ML) technologies for Medical Text Analysis.

These AI Technologies include

• Natural Language Processing (NLP): Statistical ML and Deep Learning ML
• ChatGPT and GPT-4
• Generative AI

LPBI Group is in the admirable position of sitting on a treasure trove of medical literature that would be useful input in the current environment of customized ChatGPTs looking for reliable medical content.

In the Drug Development (DD) field, AI technologies are been employed  chiefly, for these tasks:

(a) Generation of molecular information libraries

(b) Explorations and combinatorial experiments on protein structures, and

(c) measurements of biochemical interactions

The A.I. learns from patterns in the data to suggest possible useful drug candidates, as if matching chemical keys to the right protein locks.

Because A.I. for drug development is powered by precise scientific data, toxic “hallucinations” are far less likely than with more broadly trained chatbots. And any potential drug must undergo extensive testing in labs and in clinical trials before it is approved for patients.

“Generative A.I. is transforming the field, but the drug-development process is messy and very human,” said David Baker, a biochemist and director of the Institute for Protein Design at the University of Washington.

As of December 2023,

• 24 AI-discovered molecules had completed Phase I trials, with 21 of them being successful. This success rate of 80–90% is higher than the historical industry average of 40–65%. 
• In Phase II trials, the success rate is around 40%, which is similar to the historical average. 

SOURCE

AI Overview

https://www.google.com/search?q=A.I.-developed+drugs+are+in+clinical+trials&oq=A.I.-developed+drugs+are+in+clinical+trials&gs_lcrp=EgZjaHJvbWUyBggAEEUYOTIHCAEQIRigATIHCAIQIRigATIHCAMQIRigAdIBCTIxNzZqMGoxNagCCLACAQ&sourceid=chrome&ie=UTF-8

Examples of drugs developed by AI technologies:

NCI definition of AI Drugs:

AI drug

A drug that blocks the activity of an enzyme called aromatase, which the body uses to make estrogen in the ovaries and other tissues. Blocking aromatase lowers the amount of estrogen made by the body, which may stop the growth of cancer cells that need estrogen to grow. AI drugs are used to treat some types of breast cancer or to keep it from coming back. They may also be used to help prevent breast cancer in some women who are at a high risk of developing it. Examples of AI drugs are anastrozole, letrozole, and exemestane. AI drugs are a type of hormone therapy. Also called aromatase inhibitor.

 

Examples of AI drugs are anastrozole, letrozole, and exemestane. AI drugs are a type of hormone therapy. Also called aromatase inhibitor.

SOURCE

https://www.cancer.gov/publications/dictionaries/cancer-terms/def/ai-drug

More examples of AI Drugs, Drugs developed with AI technologies

#1: 

• Schrödinger’s AI-driven platform

  Uses predictive modeling to optimize the molecular structure of drugs. AI is expected to integrate more advanced simulation techniques, such as quantum computing, to more accurately predict molecular behavior.

Drug discovery software developer Schrodinger Inc. (NASDAQ: SDGR) stock has been trying to recover after plummeting over 80% off its all-time high of $117 in January 2021. Schrodinger’s artificial intelligence (AI) powered software technology platform utilizes physics-based modeling and sophisticated machine learning algorithms to help clients identify the suitable molecules to treat the desired ailments. Its programs can help predict the behavior of molecules and potential outcomes.

This entails finding suitable molecules that effectively target specific cells and proteins, transcend through cell walls, are absorbed and dissolved well without interfering with other drugs or producing bad reactions to other drugs, and are scalable.

Big Name Pharma Customers of Schrödinger, Inc.

Its technology platform allows for the faster and cheaper discovery of novel molecules with a higher success rate than traditional methods. Its clients include the top 20 pharmaceutical companies in the world, including Pfizer Inc. (NYSE: PFE), Merck & Co. Inc. (NYSE: MRK), Takeda, AstraZeneca PLC (NYSE: AZN), and GlaxoSmithKline plc  (NYSE: GSK). It closed new agreements with Eli Lilly & Co. (NYSE: LLY) and Otsuka Pharmaceuticals out of Tokyo, Japan.

SOURCE

Schrodinger is an AI-Powered Drug Discovery Developer to Watch

https://www.nasdaq.com/articles/schrodinger-is-an-ai-powered-drug-discovery-developer-to-watch

Schrodinger’s Pipelines include:

https://www.nytimes.com/2024/06/17/business/ai-drugs-development-terray.html?smid=nytcore-ios-share&referringSource=articleShare

Five AI drug discovery companies you should know about

1. Atomwise 
2. Cradle 
3. Exscientia 
4. Iktos 
5. Insilico Medicine 

According to Grand View Research, the global AI in drug discovery market size was valued at $1.1 billion in 2022, and is expected to expand at a compound annual growth rate (CAGR) of 29.6% from 2023 to 2030. The report states that the growing demand for the discovery and development of novel drug therapies and increasing manufacturing capacities of the life science industry are driving the demand for AI-empowered solutions in the drug discovery processes. 

As this report suggests, AI for drug discovery is clearly a growing field within the biopharma industry. Inevitably, as it grows even larger, we will see more companies come to the forefront of the field, hoping to change the face of drug discovery – and also the biopharma industry as a whole – so that the entire drug development process can become faster, more consistent, more accurate, and more scalable.

SOURCE

https://www.labiotech.eu/best-biotech/ai-drug-discovery-companies/#:~:text=to%20%2433%20million.-,Exscientia,manner%20using%20its%20AI%20technology.

At LPBI Group, Of Note is our Journal PharmaceuticalIntelligence.com

it represents our commitment to AI technologies in the following research categories and How many articles have been written in each of these topics: 

• A total of x articles have been categorized 511 times among the following Artificial Intelligence research categories

Artificial Intelligence – General

113

An executive’s guide to AI

9

Artificial Intelligence – Breakthroughs in Theories and Technologies

94

Artificial Intelligence Applications in Health Care

81

Artificial Intelligence in CANCER

29

Artificial Intelligence in Health Care – Tools & Innovations

55

Artificial Intelligence in Medicine – Application for Diagnosis

44

Artificial intelligence applications for cardiology

21

AI-assisted Cardiac MRI

9

Artificial Intelligence in Psychiatry

5

Artificial Intelligence in Medicine – Applications in Therapeutics

50

LPBI Group’s involvement in Conceptual Drug Development covers the following two areas:

DrugDiscovery @LPBI Group, 2016 – 2018

Synthetic Biology in Drug Discovery, 2021 – Present

Applications of Artificial Intelligence to Medicine

Artificial Intelligence: Genomics & Cancer, 2021 – Present

Medicine with GPT-4 & ChatGPT, 2023 – Present

• ChatGPT applied to Cardiovascular diseases: Diagnosis and Management

• ChatGPT applied to Cancer & Oncology

• ChatGPT and AI Algorithms applied to Medical Imaging & Radiology

LPBI Group commitment to Medical Text Analysis using Machine Learning

2021-2025 Medical Text Analysis (NLP), 2020 – Present

ChatGPT + Wolfram PlugIn, 2023 – Present

LPBI Group Team members published two books on Drug Delivery Technologies

We had covered drug delivery technologies in two of our books. See all the Books: 

https://www.amazon.com/s?k=Aviva+Lev-Ari&i=digital-text&rh=n%3A133140011&ref=nb_sb_noss

• Series E, Volume Four 

Medical 3D BioPrinting – The Revolution in Medicine, Technologies for Patient-centered Medicine: From R&D in Biologics to New Medical Devices. 

https://www.amazon.com/dp/B078QVDV2W

and

• Series C, Volume Two 

Cancer Therapies: Metabolic, Genomics, Interventional, Immunotherapy and Nanotechnology in Therapy Delivery (Series C Book 2).

http://www.amazon.com/dp/B071VQ6YYK

The Table of Contents of these two book can be found in our

Spanish-language Edition, as well

• Serie E, Volumen 4

Bioimpresión médica en 3D: la revolución de la medicina: Tecnologías para una medicina centrada en el paciente: de la I+D en agentes biológicos a los nuevos … en el paciente nº 4) (Spanish Edition) 2023

(Spanish Edition) Kindle Edition

https://www.amazon.com/dp/B0BRNVDB1P $56

• Serie C, Volumen 2

Tratamientos contra el cáncer: Metabólicos, genómicos, intervencionistas, inmunoterapia y nanotecnología para la administración de tratamientos (Serie … y la oncología nº 2) 2022

(Spanish Edition) Kindle Edition

http://www.amazon.com/dp/B0BQTM44SM $75