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Showing posts with label #collaborative creativity. Show all posts
Showing posts with label #collaborative creativity. Show all posts

Thursday, March 21, 2024

Use of Tradition, Creativity, Imagination and Technology Innovation in Propofol Manufacturing

Title in itself can be questioned by some or many for any and every discussion. It should not be, if we look at everything that is manufactured. Everything starts from rudimentary paper concepts  with subsequent intervention of humans and science that makes the products and their manufacturing process elegant, useful and easy to use. It is well known that creativity and imagination when applied to any product and/or process leads to excellent results. Perspective presented is my own and there is no relationship or influence of any profit, nonprofit organization or regulatory body.

 

Methodologies used for process development and manufacture of fine/specialty chemicals which includes active pharmaceutical ingredients (API) are same. APIs are younger cousin of fine/specialty chemicals. However, they are treated differently even when exactly the same/similar chemicals, processes and equipment are used to produce each of the molecules. The only difference is API’s cure a disease whereas fine/specialty chemicals enhance lifestyle (1). It is true that APIs have to follow stricter regulations as they are used to cure diseases. Pseudo-assumption that APIs are nobler than their older cousin, fine/specialty chemicals, is unnecessary and very convoluted. 

 

If one traces a chemical molecule being developed in a laboratory equipment and has been synthesized It uses same/similar in every process development. Paper chemistries are tested and tweaked to create a process that the developer considers to be economic and optimum. Real test of this hypothesis comes when the process is commercialized.  

 

Every chemical entity for its production has a defined process and method. Even though I have reviewed and presented my perspective (1,2,3), it is never redundant to re-visit and share steps I would take to develop and commercialize a product. My team “THE VILLAGE” (1,2,3) will include a chemist, a chemical engineer, an accountant (can be a chemist and/or chemical engineer who is well versed in cost analysis), quality control, purchasing and manufacturing. Extent of their involvement will vary as the project progresses.

 

Every fine/specialty chemical plant that includes active pharmaceutical ingredient (API) should follow the outlined or equivalent path/s (1,2,3). There is value in this methodology or similar practices. They are documentation of reason and rationale for the process design and its basis. They assist in every regulatory filing and facilitates every trouble shooting and expansion if needed. 

 

Village (1, 2, 3) has to address each of the following items. If a village is not involved from inception, costs can be higher and commercialization can be delayed.


1.     Product volume per year

2.     Physical, chemical properties, mutual behavior and toxicity of raw materials, intermediates 

3.     Mass balance

4.     Process chemistry and manufacturing methods/procedures (unit processes)

5.     Process equipment and metallurgy (unit operations)

6.     Method/s used to feed the raw materials and transfer intermediate reaction products

7.     Raw material and Product specifications

8.     Effluent/waste treatment

 

Table 1: Information needed for an excellent chemical synthesis process

 

Collected information (1,2,3) Table 1 gives significant clues about the process. To every experienced chemists and chemical engineer it gives clues about how to finesse and capitalize on mutual behavior of chemicals. This information influences product cost and process economics. If the process involves multiple reaction steps and can be fitted in the existing equipment, it is very likely that the process will be inefficient and repeated analysis of process intermediates and the final product would be necessary, a characteristic of a classical batch process. Such processes for APIs would have low asset utilization (4).

 

If a product is a high volume product and the process involves multiple steps i.e. sequential processing steps without interruption, it can be conducive to a continuous process. Every village (1, 2, 3) team member has to be familiar with the development and commercialization process. Such processes are economic. However, generally this methodology has not been part of the API landscape. For a process to be a continuous process (5) product has to have sufficient volume (Kg/year) to operate 24 hours per day, seven days per week and about 50 weeks per year with some allocated downtime for maintenance. For such processes equipment design will be product specific.   

 

Based on my experiences any product that has multiple synthesis steps when fitted in the existing equipment  is generally a batch process. Fitting processes in existing equipment have inherent drawbacks of poor design and less than efficient asset utilization. Excess solvents, water or organic/s, are needed to assure proper processing. They have high emissions (6, 7). Along with low process productivity process yields are generally less than optimum. 

 

Continuous processes are not adopted by the brand pharma companies. Reason is simple. Speed to market. Once the product’s efficacy is recognized, it is submitted for regulatory approval. That is the key. Since the market size is not defined, batch process is the selected process. Any process changes require regulatory reapproval and that can be very expensive. In addition, village is not involved in their business model. This can delay the commercialization of process. For the generics many APIs of high volume can be produced using continuous process but will necessitate different business model. Only an outlier company will consider such options (1,2,3, 8). 

 

Manufacture of Propofol: 

 

Five alternate refenced chemistries (9,10,11,12,13) for the manufacture of Propofol are presented. Items discussed in Table 1 have to be incorporated. Village team should review each of the experiments in the lab to get a feel for the process, flow of materials and mutual behavior of chemicals. This can unleash their creativity and imagination and would facilitate the scale up and commercialization of an excellent process. Raw materials should be of commercial grade quality and do not need to be pharmaceutical grade i.e. high purity. They are expensive and add unnecessary cost and may not be any different from the commercially available raw materials. Quality of the final product has to be the final driver. 

 

Raw materials for Propofol synthesis (9,10,11,12,13) Table 1 influence process design and selection. Chemistries described (9,10,11,12) are similar. In reference (13), the starting material is different. De-carboxylation step is executed differently. For process selection each of the outlined process chemistry needs a thorough review. 

Execution of laboratory processes in the plant will be very different from what is being discussed in these papers and patent. Again, each process has to reviewed carefully. Described chemistries (9, 10, 11, 12)  present an excellent opportunity for a continuous process (5). Purification or distillation of Propofol is based on chemical engineering distillation practices and there is no novelty. 

 

Items of Table 1 can be applied to select the best and the simplest process. Since 4-Hydroxybenzoic acid is solid at room temperature, its addition can be controlled if it is used as a melt or in a solvent that has high solubility. Scheme one (9)because of its simplicity could be the most likely candidate for a continuous process. 

Stoichiometry and process conditions can be precisely controlled and make an excellent case for a continuous process (1). Depending on the process selection (batch vs. continuous) design, feeding of aluminum chloride (2) has to carefully thought through. 

Chemical

4-Hydroxybenzoic  

           acid                  

3,5-di-isopropyl-4-hydoxybenzoic acid

Methylparaben

Propofol

 

CAS No.

99-96-7

13423-73-7

99-76-3

2078-54-8

Formula

C7H6O3

C13H18O3

C8H8O3

C12H18O

Mol. Wt.

138

222

152

178

Melting point, ºC

214.5

146

~ 125

18

Boiling point, ºC

 

345

~ 299

256


Table 2: Properties of Reactants and Propofol 

Yearly production volume is a very important criterion for selection of a batch or continuous process. Since propofol is a widely used for anesthesia its global use would be high. Sales of finished Propofol speculated by many, too many to cite. For Propofol as API no numbers were available. With consultation of Dr. Albinus D’Sa (16), it is estimated that between 250,000 to 300,000 MT per year would be needed to meet global needs. 

 

Since Propofol is a generic product only a new entrant in the business would use what has been described but the principles and methodology can be used by any fine/specialty and API business. 

 

 We have to remember that every multiple step chemical synthesis is an opportunity to simplify the process. This is easier said than done. Total knowledge and command of the chemicals used and produced in the process is a MUST. Knowledge of the unit operations (14) and chemical and physical properties (1, 2, 3) is essential. Application and inclusion of the knowledge simplifies the process and give command to produce quality product whether it is a batch (15) and/or a continuous process (6). A distinct advantage of a continuous process is that it can be ramped up to meet sudden surge in product demands. 

 

Some of the discussion above has been reviewed earlier (1, 2, 3, 8). Use and inclusion of parameters outlined in Table 1 allows proper process equipment (1) design and can reduce investment. Since Propofol is already commercial most likely not much will change unless an outlier company decides to enter the business. For any outlier it would be necessary to know the yearly demand for the Propofol API.


For process selection (batch vs. continuous) global how much active Propofol is produced is not available. Only number available is projected speculation of finished product. That does not give a reliable number. After consultation and discussion with Dr. Albinus D’Sa (16), different anesthesiologists, published information (17, 18) and world population (19) best number has been calculated, Table 3. Total Propofol active molecule needed is large enough to have an excellent continuous process. Continuous operations can be ramped to meet fluctuating active molecule need. 

Sweden Population 

10 million (18)

Yearly use, kg

394

Global population 

8.1 billion (19)

Yearly Global Propofol need, kg

250,000 to 305,000 

 

Table 3: Estimated Global Propofol Active Ingredient need

Similar analysis can be done for many other products. Options exist for continuous processes for many other products exist and need a review along with business model change. They can be used to alleviate shortages. 

 

Girish Malhotra, PE

 

EPCOT International 

 

References:


1.     Malhotra, Girish:  Active Pharmaceutical Ingredient Manufacturing: Nondestructive Creation De Gruyter April 2022

2.     Malhotra, Girish: Chemical Process Simplification: Improving Productivity and Sustainability  John Wiley & Sons, February 2011 

3.     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

4.     Benchmarking Shows Need to Improve Uptime, Capacity Utilization, Pharma Manufacturing Sep 19, 2007

5.     Continuous Processing Accessed February 12, 2024

6.     Burke, J. What does net zero mean?, May 2, 2019 Accessed April 27, 2021

7.     Sheldon R.A. The E factor 25 years on: the rise of green chemistry and sustainability, Green Chemistry, 2017, 19, 18-43 Accessed February 17, 2021

8.     Profitability through Simplicity

9.     Pramanik  C. et. al. Organic Process Research Development, 2014, 18, 152-156

10.  Mougeot, R. et al Continuous Flow Synthesis of Propofol. Molecules 2021, 26, 7183

11.  Guilherme M. Martins et. al. Scaled up and telescoped synthesis of propofol under continuous-flow conditions Journal of Flow Chemistry (2022) 12:371–379 , 

12.  SCHNEIDER, Jean-Marie et.al. Process for producing Propofol WO/2023/111488  

13.  USP 11,767,281 B2

14.  Unit operations of Chemical Engineering, McCabe, W.L. Smith et. al McGraw Hills Inc. 1993, Accessed February 17, 2024

15.  Batch Production Wikipedia Accessed July 6, 2017

16.  D’Sa, Albinus Dsa Pharma Associates,

17.  Braun B: Miljöinformationen för propofol är framtagen av företaget Aspen Nordic för Diprivan 

18.  Sweden population https://www.worldometers.info/world-population/sweden-population/

19.  World population https://www.worldometers.info/world-population/














 















 

Friday, March 31, 2023

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