Considerations to have an excellent environmentally friendly and economic chemical process?

We are taught chemistry and chemical engineering fundamentals and learn many of the tools through education and experience . We use our creativity and experience to string them together to create and commercialize good chemical synthesis processes. It is a never ending task and that is why it is called “process of continuous improvement”. This has been enumerated ^{(1, 2, 3, 4, 5)} and other references (too many to cite). With time we augment our experiences and continue to develop better processes. This is the Law of Nature.  

All of the views presented are mine and not influenced by any regulatory body or any profit/non-profit entity. Readers are more than welcome to add to the discussion and improve the process as they see fit. 

Synthesis of manufacture of pantoprazole outlined in Figure 1 USP 8,691,995 ⁽⁶⁾ is used as an example. 

                        

                                  Figure 1: Pantoprazole synthesis USP 8,691,995 ⁽⁶⁾

 

For creating and commercializing processes that are economical and have the lowest “E-Factor ⁽⁷⁾” we have to include and capitalize on mutual behavior of every chemical used and produced in every reaction step. Such review process begins as soon as we pen a viable chemical reaction. Village ⁽⁴⁾ has to be involved from inception of the process. Discussion and review is necessary for every chemical synthesis and formulation process ^{(1, 2, 3, 4, 8)}. They reduce commercialization time. 

 

First and the foremost thing necessary for the process is to write a mass balance of the process and identify physical and chemical properties of each reactant used and product/byproduct produced. Solubility of each chemical in different solvents is extremely helpful as it tells us how we can use solvents to have an excellent process. It is well documented that every reaction is best carried out in liquid phase ^{(4, 5, 8)}. This information can be used to incorporate value of physical properties ^{(1, 2, 3, 4, 5, 8)} i.e. relative solubility and insolubility, density differences, corrosivity, melting and boiling point etc. These might be considered valueless and/or mundane by many but are the guiding force and facilitator behind every good process design ^(4,8). They make the basis of equipment and process design.  

 

Most of the reactants are solid at room temperature. Their melting points can be high. Thus, they will have to be dissolved in a solvent. Solvent selection is critical. It should be such that they can dissolve or have a concentrated pumpable slurry. Uniform and well dispersed slurry can be easily metered for stoichiometric control. Since bleach and NaOH are used in the process ⁽⁶⁾ under discussion, their solubility/insolubility in water and other components has to be a consideration for this synthesis.   

 

In Step 1 sulfur dioxide is generated. In absence of water it is not corrosive but has to be handled safely. Proper material of construction for equipment is necessary. In step #3 bleach is used. Corrosion resistant equipment like glass will have to be used. If acids are used in the reaction and/or generated in the reaction, attention needs to be paid to material of constriction for the equipment used. 

 

Methylene chloride is acceptable and widely used for laboratory synthesis. However, consideration of alternate solvent/s for every commercial process alternate solvent/s that will simplify and improve the process is extremely important. Can the reaction be carried at higher temperature to speed the reaction ^{(1, 2, 4, 9)} has to be a consideration? Most likely it can be and that would require a different solvent of higher boiling point. Such options cannot be readily tested in laboratory development. Their water solubility and reuse will have to be a consideration. Use of higher boiling point solvent could allow the first reaction step ⁽⁶⁾ to carried out at a higher temperature. This can improve the reaction rate. We know that every ten degrees rise in temperature doubles the reaction rate ⁽⁹⁾.  

 

In the production of pantoprazole sulfide, step 2 ⁽⁶⁾, to facilitate the reaction patent calls for use of phase transfer catalyst. If the immiscibility of the reactants can be improved by alternate means such as feeding the reactants in confined space e.g. a miniature/confined space or use of in-line static mixer, it may be possible to eliminate the use of phase transfer catalyst and process simplified. In-line static mixers have been available for over fifty years. Such devises are not available to the chemists in the labs at majority of companies. In addition, most of the chemists and chemical engineers generally due to limited production volume per year do not consider such options as they would be considered too adventurous for any fine/specialty chemical or active pharmaceutical ingredient (API) producer.

 

In the conversion of pantoprazole sulfide to pantoprazole base bleach is used. This is a significant improvement over the use of m-chloroperoxybenzoic acid that was used in the preparation of Omeprazole ⁽¹⁰⁾. M-chloroperoxybenzoic acid is expensive and a challenge to handle compared to common bleach used in ⁽⁶⁾. Use of bleach in similar reactions ⁽¹¹⁾ has been practiced in the production since 1967. This suggests that literature and patent search from the inception of process development is critical as it can simplify and speedup process development.  

 

Pantoprazole like Omeprazole is a high volume API drug and can be produced using a continuous process. Based on my review both are still produced using batch processes ^{(12, 13)}. 

 

As suggested earlier, it is important that the village ⁽⁴⁾ be involved from process inception. Patents and literature are a treasure trove of knowledge and experience. They need to be exploited and used for creating better manufacturing processes. Use of equipment that is commercial and being used in other applications can be exploited ⁽⁴⁾. Scale up and to the market time will be reduced. Commercialized processes not only will be economic but will have significantly lower emission (E) factor ⁽⁷⁾. 

 

Girish Malhotra, PE

 

President,

 

EPCOT International

1. Malhotra, Girish: Chemical Process Simplification: Improving Productivity and Sustainability John Wiley & Sons, February 2011 
2. Malhotra, Girish: Chapter 4 “Simplified Process Development and Commercialization” in “ Quality by Design-Putting Theory into Practice” co-published by Parenteral Drug Association and DHI Publishing© February 2011
3. Malhotra, Girish: Research Report: Strategies for Improving Batch or Creating Continuous Active Pharmaceutical Ingredient (API) Manufacturing Processes, March 2017; AVAILABLE FREE
4. Malhotra, Girish: Active Pharmaceutical Ingredient Manufacturing: Nondestructive Creation De Gruyter April
5. Malhotra, Girish: Profitability through Simplicity
6. Kankan, R. N. et.al. USP 8,691,995 B2  2014, Process, Cipla Limited 
7. Sheldon R.A. The E factor 25 years on: the rise of green chemistry and sustainability, Green Chemistry https://pubs.rsc.org/en/content/articlelanding/2017/gc/c6gc02157c/unauth#!divAbstract , 2017, 19, 18-43 Accessed February 17, 2021
8. Malhotra, Girish: Sociochemicology May 30, 2013 
9. Chemical reaction rate and temperature relationship https://chem.libretexts.org/Bookshelves/Physical_and_Theoretical_Chemistry_Textbook_Maps/Map%3A_Physical_Chemistry_for_the_Biosciences_(Chang)/09%3A_Chemical_Kinetics/9.05%3A_The_Effect_of_Temperature_on_Reaction_Rates
10.  Brändström, Arne: USP 5,386,032, 1995, Method of synthesis of 5-methoxy-2-[(4-methoxy-3,5-dimethyl-2-pyridinyl)-methyl]sufinyl-1-H benzimidazole (omeprazole), Aktiebolaget Astra, Sodertalje, Sweden
11. Hill, D. R. et. al. USP 3,324,119, 1967, Production of Isatoic anhydride and Certain Halo Derivatives Thereof, Maumee Chemical Company, Toledo, Ohio 
12. Malhotra, Girish: Alphabet Shuffle – Moving from QbA to QbD, Pharmaceutical Processing world, February 2009 Accessed August 20, 023
13.  Malhotra, Girish: Analysis of API (Omeprazole) AIChE Nashville National Meeting 2009 

Artificial intelligence in Chemical Process Development, Manufacturing & Net Zero

Artificial Intelligence (AI) ⁽¹⁾ is becoming the latest go to technology/methodology for almost every application. Numerous articles have been published in the areas of chemical properties, discoveries, process design and development and manufacturing areas ^{(2,3,4,5,6,7)}. If the machine language can be used to simplify conventional chemical process development and design, it is my speculation that commercialization of products can be sped up multifold. Chemical manufacturing landscape could change dramatically. This will lead to improved profits through faster availability and reduced shortages of products in every segment of the chemical industry that includes fine/specialty chemicals, additives, cosmetics, flavors and fragrances and pharmaceuticals. In addition, every chemical related business can make significant progress towards “net zero” ^(8,9) emissions.   

 

I am presenting my perspective on how AI could be used to develop, simplify, speed up development, commercialization and manufacturing of the products. Perspective presented here is my own. There is no financial relationship with any “for profit” and nonprofit organization.

 

AI and Process Development:

 

For most of the product categories mentioned above development and commercialization take their own course. This is due to availability of data such as properties and mutual behavior of the chemicals needed and used in product evaluation, formulation and process design. Development moves from the laboratory to commercial scale following their established paths that have been taught and practiced over the last 70+ years. 

 

For product development physical and chemical properties of chemicals are needed. Much of the data about chemicals (physical and chemical properties, safety and health value of the chemicals) used and produced might be available from Chemical Abstract Services ⁽¹⁰⁾ NIST Chemistry Web Book ⁽¹¹⁾, product suppliers and can be generated internally at the companies. AI should accelerate and facilitate availability of solubility and safety data. Safety data and solubilities of solvents identified by AI would have to be verified in the laboratory. It could also be used to define process conditions for chemical processing. Process development and commercialization will be accelerated.

 

Many of the chemicals are raw materials are solid at ambient temperatures. To facilitate processing and ease of handling, they are solubilized or slurried in inert solvent/s. These are recovered and reused. This has been the tradition for the last century. Even though the solvents are recovered and reused, they still leave a large environmental footprint than a process which is all liquid process i.e. solids do not have to be slurried to facilitate processing. 

 

Sociochemicology ^{(12, 13)} i.e. mutual behavior of chemicals plays a significant part in development and commercialization of chemical synthesis processes. Some of the methods that can be used to facilitate incorporation of physical properties of the chemicals are reviewed ^(14,15). However, the methods should not be limited to what has been discussed in literature. 

 

Some of the methods that value use of liquids in chemical processing are reviewed ⁽¹⁶⁾. Between AI and “collaborative creativity” ⁽¹⁷⁾ of the village ⁽¹⁶⁾ excellent processes can be developed. I believe that with the help of artificial intelligence it can and will become possible, if it is not already being tried. Having knowledge that all liquid processes could minimize solvent use would be giant leap to “Net Zero” processes. Developers can take advantage of point of addition and heat of reaction to control the reaction kinetics to speed up the processes. 

 

Having an all liquid process could lead to use of smaller size reactors or alternate reaction systems ⁽¹⁶⁾ that could eliminate or significantly reduce the amount of solvent use. It would be a significant step to achieving “Net Zero”. 

 

I believe that AI could scour the processing equipment world and propose equipment that is commercially used in chemical and other industries and would be suitable for the chemical synthesis and blended product applications. It will be interesting to see how AI will change chemical engineering practices. My conjecture is that it could propose processing methods and sequences that would simplify chemical process manufacturing and further augment “collaborative creativity” ⁽¹⁶⁾ of the “village” ⁽¹⁵⁾. Business models should improve.  

 

For the AI proposed designs my expectation is that the unit processes and unit operations might not change much from traditional ways but not having seen any such design it would enlightening to see the results of what will change. Proposed process designs would be readily accepted in the companies after they have been tested internally and product quality meets or exceeds expectations. Adoption in most companies will come quickly. However, companies that are regulated e.g. pharmaceuticals will be skeptical and apprehensive. This will be due major regulatory acceptance challenges as most of the regulatory folks have essentially no or very little chemical process development, design, commercialization and manufacturing experience. Lack of the knowledge and experience at regulators could be a major expenditures and time delays as the regulators will have to be taught value of better technologies. There will be cost implications to the companies and they might not or be slow to venture out in using AI based designs for their product development and manufacturing.  

 

Brand pharma companies could adopt the AI based technologies quickly as they are single product focused. However, generics since they are fragmented and do not have dedicated equipment could be reluctant to accept better technologies that could be AI generated. If AI based manufacturing is accepted overall equipment running time in pharmaceuticals could be lower than the current times. This might deter adoption of AI based technologies. Regulations would have to re-written. 

 

With the progress that is being made in AI it is expected that process development and manufacturing technologies will be of great benefit to humanity ^{(18, 19)}. With the changing landscape regulators will have change their posturing especially when it comes to pharmaceutical product approvals. If they don’t and will not keep up with time, stone age will be a burden on space age needs. 

 

Tomorrow is here:

 

Some might say AI will arrive tomorrow. However, we all know that TOMORROW never comes. AI’s TOMORROW is HERE. We have to learn and capitalize on what we do especially when it comes to chemical products and processes. Listening to the linked ^{(20, 21, 22, 23)} my conjecture is that it will have a powerful impact on chemical process synthesis and could deliver us pathways and processes that we think are or thought to be impossible. Acceptance in chemical process development, design and commercialization could be fast in non-FDA approved products. Incorporation of AI in drug development could be fast. However, as suggested earlier, incorporation of AI in manufacturing could lag “quite” some time due to regulator’s lack of hands on knowledge and experience in product, process development, design and manufacturing practices. My conjecture is that combination of “Creative Destruction” ^{(24, 25)} and “Nondestructive Creation” ^{(16, 26)} will come in play. Business Models, Regulatory policies and procedures will require a monumental change. 

 

Girish Malhotra, PE

 

EPCOT International

 

1.     Artificial Intelligence, Wikipedia  https://en.wikipedia.org/wiki/Artificial_intelligence Accessed March 21, 2023

2.     Chemical Engineering And Artificial Intelligence https://aichatgpt.co.za/chemical-engineering-and-artificial-intelligence/ Accessed March 21, 2023

3.     Artificial Intelligence In Chemical https://aichatgpt.co.za/artificial-intelligence-in-chemical-engineering/#AI_For_Developing_Novel_Chemicals_and_Products Accessed March 22, 2023

4.     Stephanopoulos, G. Artificial Intelligence in Process Engineering, Chemical Engineering Education https://journals.flvc.org/cee/article/view/124525/123536 pg. 182-185, 192 Accessed March 21, 2023

5.     Lou, H. H., Gai, H. Lamar University, How AI can better serve the chemical process industry, July 2020 Accessed March 21, 2023

6.     Trinh, C.; Meimaroglou, D.; Hoppe, S. Machine Learning in Chemical Product Engineering: The State of the Art and a Guide for Newcomers. Processes 2021, 9, 1456. https://doi.org/10.3390/pr9081456 Accessed March 21, 2023

7.     Gasteiger J.: Chemistry in Times of Artificial Intelligence ChemPhysChem 2020, 21, 2233– 2242 Accessed March 21, 2023

8.     Burke, J. What does net zero mean? https://www.greenbiz.com/article/what-does-net-zero-mean, May 2, 2019 Accessed April 27, 2021

9.     Sheldon R.A. The E factor 25 years on: the rise of green chemistry and sustainability, Green Chemistry https://pubs.rsc.org/en/content/articlelanding/2017/gc/c6gc02157c/unauth#!divAbstract , 2017, 19, 18-43 Accessed February 17, 2021

10.  Chemical Abstract Service https://www.cas.org/cas-data Accessed March 21, 2023

11.  NIST Chemistry Web Book SRD 69 https://webbook.nist.gov/chemistry/ Accessed March 21, 2023

12.  Malhotra, Girish: Process Simplification and The Art of Exploiting Physical Properties, Profitability through Simplicity March 10, 2017 Accessed March 21, 2023

13.  Malhotra, Girish: Sociochemicology, 2014 Accessed March 21, 2023

14.  AI for chemistry https://chemintelligence.com/ai-for-chemistry Accessed March 21, 2023

15.  Butler, Keith T. et.al Machine learning for molecular and materials science, Nature volume 559, pages 547–555 (2018) Accessed March 22, 2023

16.  Malhotra, Girish: Active Pharmaceutical Ingredient Manufacturing: Nondestructive Creation April 19, 2022 https://www.degruyter.com/document/doi/10.1515/9783110702842/html

17.  Malhotra, Girish: API Manufacturing and Environmental Sustainability Chemistry Today, September/October 2022 Vol. 40(5)

18.  Artificial Intelligence In Chemical Engineering https://aichatgpt.co.za/artificial-intelligence-in-chemical engineering/#AI_For_Developing_Novel_Chemicals_and_Products Accessed March 22, 2023

19.  Chemical Engineering And Artificial Intelligence https://aichatgpt.co.za/chemical-engineering-and-artificial-intelligence/ March 21, 2023

20.  A360 Day 1 Emad Mostaque https://www.youtube.com/watch?v=aEWHrqxniLM Accessed March 24, 2023

21.  Bubeck S. et.al. Sparks of Artificial General Intelligence: Early experiments with GPT-4, https://arxiv.org/pdf/2303.12712.pdf Accessed March 24, 2023

22.  Gates Bill: AI and the rapidly evolving future of computing https://www.youtube.com/watch?v=bHb_eG46v2cAccessed March 24, 2023

23.  Gates Bill, The Age of AI has begun https://www.gatesnotes.com/The-Age-of-AI-Has-Begun March 21, 2023 Accessed March 25, 2023 

24.  Malhotra, Girish: Is "Creative Destruction" the way to go for the Pharmaceuticals? Profitability through Simplicity, December 12, 2008 Accessed March 22, 2023

25.  Creative Destruction Schumpeter: Definition https://youmatter.world/en/definition/creativedestruction-schumpeter-definition/ April 20, 2020 Accessed August 15, 2022 

26. Kim, Chan W., Mauborgne: Nondisruptive Creation: Rethinking Innovation and Growth, MIT Sloan Review, February 21, 2019