pharmaceutical applications of Artificial intelligence

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1. A RTIFICIAL I NTELLIGENCE (AI), R OBOTICS AND C OMPUTATIONAL FLUID DYNAMICS (CFD) 1 6 J u n e 2 21 1

2. CONTENTS 2 G e n e ra l o v erview Pharm a c e utic a l A u tom a tion Ph a rma c e u tic a l a p pli c ati o ns A d v a nt a g e s a n d Disa d v a nt a g e s C u r r e n t C h alle n g e s a n d F ut u r e Directi o ns

3. I NTRODUCTION TO A RTIFICIAL I NTELLIGENCE (AI) 3 According to the father of Artificial Intelligence, John McCarthy, it is “The science and engineering of making intelligent machines, especially intelligent computer programs”. Also, intelligence distinguish us from everything in the world. As it has the ability to understand, apply knowledge. Also, improve skills that played a significant role in our evolution. We c a n d e fin e AI a s the are a o f c o m p u ter scien c e. Further, they deal with the ways in which computers can be made. As th e y ma d e to perfor m c o g n itive fun c tions a scr i b e d to hum a ns .

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5. Artificial Intelligence (AI) refers to the ability of a computer or a computer- enabled robotic system to process information and produce outcomes in a manner similar to the thought process of humans in learning, decision making and solving problems. B y extensi o n , the goa l o f A I system s is to de velo p s y stems capable of tacking complex problems in ways similar to human logic an d reasoning. Artificial intelligence – AI – is getting increasingly sophisticated at doing what humans do, albeit more efficiently, more quickl y , 88 an d more cheaply. While AI an d rob o ti c s ar e becomin g a natura l par t o f our everyday lives, their potential within healthcare is vast. 5

6. Artificial Intelligence is a new electronic machine that stores large amount o f information a n d pro c es s it a t v e r y hi g h s p e e d . The computer is interrogated by a human via a teletype It passes if the human cannot tell if there is a computer or human at the other end. T h e a b ili t y to sol v e the pr o bl e ms. It is the science and engineering of making intelligent machines, especially intellige n t c o m p ut e r pro g rams. It is related to the similar task of using computers to understand human intelligence. B r ie f hi s tory o f A I: 1941- First electronic computer (technology finally available) 195 6 - T e r m a rt i ficia l int e llien c e intro d u c e d . 1960s- Checkers –playing program that was able to play with opponents. 1980 s - Q u alit y c o ntro l sys t em. 2000- First sophisticated walking robot. 1 6 J u n e 2 21 6

7. OVERVIEW OF AI : Since the invention of computers or machines, their capability to p e r f or m v a riou s tasks w e n t o n gr o wi n g e x p o n e nti a lly. H u ma n s h a v e d e v e lo p e d the p o w e r o f c o m p u ter sys t em s in terms of their diverse working domains, their increasing speed, and reducing s i z e with r esp e c t to tim e . A branch of Computer Science named Artificial Intelligence pursues cre a ting the c o m p ut e r s o r m a c h in e s a s intellige n t a s h u man b e in g s. 7

8. PHILOSOPHY OF AI 8 While exploiting the power of the computer systems, the curiosity of human, lead him to wonder, “Can a machine think and behave like h u m a ns d o ?” Thus, the development of AI started with the intention of creating similar intelligence in machines that we find and regard high in humans. Goals of AI To Cre a te E x p e r t Sys t ems. To Impl e m e n t Hu m a n Intellig e n c e in Ma c hi n es.

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10. P ROGRAMMING W ITHOUT AND W ITH AI 10

11. W HAT IS AI T ECHNIQUE ? In the real world, the knowledge has some unwelcomed properties : It s v o lume is h u g e , n e x t t o unim a gi n a b le. It is not well-organized or well-formatted. I t ke e p s c h a n gi n g c o nstantly. AI Technique is a manner to organize and use the knowledge efficiently in such a way that: It should be perceivable by the people who provide it. It should be easily modifiable to correct errors. It should be useful in many situations though it is incomplete or inaccurate. AI techniques elevate the speed of execution of the complex program it is e q ui p p e d with. 11

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13. ADVANTAGES OF AI : 13 a . Er r o r R e d u ction: We use artificial intelligence in most of the cases. As this helps us in red u cin g the ri s k. Also, i n c rease s the c h a n c e o f re a c h ing a c c u rac y with t h e gre a ter d e gre e o f p recision. b . Dif f icul t E x plor a tio n : In mining, we use artificial intelligence and science of robotics. Also, ot h e r fue l e x p loration pro cesses. Moreover, we use complex machines for exploring the ocean. Hence, o v erc o ming the o c ea n limi t atio n .

14. c . D a il y Application: As we know that computed methods and learning have become c o mm o n p la c e in d ail y li f e. Financial institutions and banking institutions are widely using AI. That is to org a ni z e a n d m a n a g e d a ta. Also, AI is used in the detection of fraud users in a smart card based system. d . Digita l A s s i s tan t s: “Avatars” are used by highly advanced organizations. That are digital assistants. Also, t h e y c a n intera c t with t h e users . H e n c e . T h e y ar e savi n g hu m an n e e d s o f resourc e s. As we can say that the emotions are associated with mood. T h a t th e y c a n clo u d ju d g m e n t a n d af f e c t h u man eff i ci e n c y . M o reov er, c o m p letely rule d o u t fo r ma c hi n e intellige n c e . 14

15. e . N o bre a k s : Machines do not require frequent breaks and refreshments for humans. As machines are programmed for long hours. Also, t h e y c a n c o ntin uo u s l y p e r f or m with o u t gettin g b o red. f . I n cr e a s e Wo r k Eff i ci e ncy: For a particular repetitive task, AI-powered machines are great with am a zin g eff i ci e n c y. Best is they remove human errors from their tasks to achieve accurate results. g. Reduce cost of training and operation: Deep Learning and neural networks algorithms used in AI to learn new thi n g s like h u m a n s d o . Also, this way they eliminate the need to write new code every time. 15

16. DISADVANTAGES OF A RTIFICIAL I NTELLIGENCE : a . Hig h C ost: Its creation requires huge costs as they are very complex machines. Also, repair and maintenance require huge costs. b . N o R e pl i c a ti n g Humans : As intellige n c e is b elie v e d to b e a gif t o f n ature. An ethical argument continues, whether human intelligence is to be replic a ted o r n ot. c . L e s s e r J o b s : As we are aware that machines do routine and repeatable tasks much b e tter th a n h u m a ns. Moreover, machines are used of instead of humans. As to increase th e ir prof i tability in b u s i n e s s es . d . L a c k o f Pe rsona l Connectio n s: 16

17. We c a n’ t rel y too m u c h o n th e s e ma c hi n e s fo r e d u c atio n a l o v ers i g h t s . T h a t h u r t learn e r s m o r e th a n h e lp. e . Ad d ictio n : As we rel y o n ma c hi n e s to m ak e e v ery d a y tasks m o r e e f f icie n t we use machines. f . Ef f icien t D e cisio n Mak i ng: As we know computers are getting smarter every day. Also, they are demonstrating not only an ability to learn but to teach ot h e r c o m p ut e r s . 17

18. APPLICATIONS OF AI IN PHARMACEUTICALS AI have various applications in health care and pharmacy which are as follows: Disease Ide n tif ic a tion Per s o n aliz e treartment Dr u g Disc o v e ry/M a n u fact u ring Clini c a l Trial R e search R a di o lo g y a n d R a di o th e rapy Smart ele c tronic h e alt h rec o rd 18

19. AI in Drug Discovery Artificial intelligence (AI) is revolutionizing drug discovery by offering substantial potential to reshape the speed and economics of the industry.Here are some ways AI is being used in drug discovery: Molecular simulations : AI is being used to reduce the need for physical testing of candidate drug compounds by enabling high-fidelity molecular simulations that can be run entirely on computers (i.e., in silico) without incurring the prohibitive costs of traditional chemistry methods Candidate drug prioritization : Once a set of promising “lead” drug compounds has been identified, AI is used to rank these molecules and prioritize them for further assessment, with AI approaches outperforming previous ranking techniques . Synthesis pathway generation : AI is being used to generate synthesis pathways for producing hypothetical drug compounds, in some cases suggesting modifications to compounds to make them easier to manufacture . Structure-based drug discovery : AI can assist in structure-based drug discovery by predicting the 3D protein structure because the design is in accordance with the chemical .

20. Predicting drug efficacy and side effects : AI is being trained to predict drug efficacy and side effects, and to manage the vast amounts of documents and data that support any pharmaceutical product . Reducing costs and time: AI algorithms have the potential to transform most discovery tasks (such as molecule design and testing) so that physical experiments need to be conducted only when required to validate results, which can reduce costs and time Flexible regulatory framework: FDA recognizes the increased use of AI/ML throughout the drug development life cycle and across a range of therapeutic areas. FDA plans to develop and adopt a flexible risk-based regulatory framework

21. Artificial intelligence (AI) is being used in pharmaceutical formulation to optimize the formulation process and obtain the desired attributes of the pharmaceutical product. Here are some ways AI is being used in pharmaceutical formulation: Quality by Design ( QbD ) & Design of Experiment (DoE) : AI is used to confirm the quality profile of drug products, reduce interactions among the input variables for optimization, and modelization and various simulation tools used in pharmaceutical manufacturing (scale-up and scale-down)1 Solid dosage forms : AI-based formulation development is a promising approach for facilitating the drug product development process. AI is used to predict drug release, detect tablet defects, and predict physical or chemical stability and dissolution rates and profiles Coatings, adhesives, plastics, vaccines, drugs, cosmetics, perfumes, inks, cleaning products : AI is used to speed up the development of many different kinds of formulations3. Drug design : AI is used extensively to improve the design techniques and required time of the drugs. Additionally, the target proteins can be conveniently identified using AI, which enhances the success rate of the designed drug. The AI technology is used in each step of the drug designing procedure, which decreases the health hazards related to preclinical trials and also reduces the cost substantially4. Manufacturing process improvement : AI is used to improve the manufacturing process of pharmaceutical products . Drug target identification and validation : AI is used to identify novel biological targets, drug repurposing, and biomarker identification . Overall, AI is being used to optimize the formulation process, reduce the use of resources, increase the understanding of the impact of independent variables over desired dependent responses/variables, and accelerate drug discovery and reduce its huge costs and the time to market for new drugs 4 .

22. Monitoring product quality : AI methods can be used to monitor product quality, including quality of packaging, by analyzing images of packaging, labels, or glass vials to detect deviations from the requirements of a product's given quality attribute Initial screening of drug compounds : AI can help manufacturers with the initial screening of drug compounds to predict the success rate of the formulations Optimizing production schedules : AI can be used to predict the optimal production schedule for a drug based on inventory levels, current demand, and the factory's capacity . Improving drug design : AI is being used extensively to improve the design techniques and required time of the mdrugs . The target proteins can be conveniently identified using AI, which enhances the success rate of the designed drug. The AI technology is used in each step of the drug designing procedure, which decreases the health hazards related to preclinical trials and also reduces the cost substantially . .

23. Process analytical technology (PAT) : AI and machine learning are being employed in PAT, which is an area that involves monitoring and controlling the manufacturing process to ensure consistent quality . Manufacturing process improvement : AI can help address issues related to efficiency and scalability at every step of the manufacturing process. Incorporating AI and machine learning in pharmaceutical manufacturing can address most of these issues.

24. AI in clinical trails Patient recruitment and screening : AI can help identify potential participants for clinical trials by analyzing electronic health records, social media, and other data sources . Trial design and optimization : AI can help optimize trial design by finding patterns in data and predicting patient behavior and drug efficacy . Safety monitoring : AI can be used to monitor patient safety during clinical trials by analyzing data from wearable devices and other sensors . Data analysis : AI can help automate data entry and analysis, reducing the time and cost associated with drug development . Medical coding : AI can be used to automatically query and code medical data, reducing the time and effort required for data cleaning . Statistical analysis : AI can help facilitate more comprehensive statistical analysis and tackle the challenging issues of missing data and missing visits

25. AI in health care Clinical decision support : AI is playing a key role in clinical decision support as it delivers data to providers to aid in diagnosing, treatment planning, and population health management . Patient diagnosis and prognosis : AI is being used to assist physicians in diagnosing and predicting the prognosis of patients by analyzing large amounts of data, such as genomic, biomarker, and phenotype data, as well as health records and delivery systems . Drug discovery : AI is being used to speed up the drug discovery process by predicting the success rate of drug formulations and identifying potential drug candidates . Prevention of diseases : AI can be used to forecast the spread of diseases at the macro level and calculate the probability that a condition may be contracted by an individual, which can help with disease prevention . Remote diagnosis : AI has the capability of remotely diagnosing patients, thus extending medical services to remote areas beyond the major urban centers of the world .

26. Administrative tasks : AI can help remove or minimize time spent on routine, administrative tasks, which can take up to 70 percent of a healthcare practitioner’s time . Medical coding : AI can be used to automatically query and code medical data, reducing the time and effort required for data cleaning 1 . Patient recruitment and screening : AI can help identify potential participants for clinical trials by analyzing electronic health records, social media, and other data sources 5 .

27. CURRENT CHALLENGES/ FUTURE ASPECT 27 Many big Pharmaceutical companies began investing in AI in order to develop better diagnostics or biomarkers, to identify drug targets and to design new drugs and products. Merck partnership with Numerate generating novel small molecule ca r diovascula r diseas e ta r get . in Mar c h 20 12 focusin g o n dru g leads fo r un n amed In December, 2016 Pfizer and IBM announced partnership to accelerate drug discovery in immunooncology .

28. I NTRODUCTION TO ROBOTICS 28 Robotics is a branch of engineering and computer science that deals with the design, construction, operation, and application of robots. The objective of the robotics field is to create intelligent machines that can assist humans in a variety of ways. Robotics can take on a number of forms, including industrial robots and robot arms used by manufacturers and warehouses. Robotics involves the integration of fields such as mechanical engineering, electrical engineering, information engineering, mechatronics engineering, electronics, biomedical engineering, computer engineering, control systems engineering, software engineering, and mathematics. The field of robotics has advanced remarkably in the last 50 years, and today's robots can execute specific tasks with little or no human intervention and with speed and precision. Robotics has a wide variety of use cases that make it the ideal technology for the future, and soon, we will see robots almost everywhere. We’ll see them in hospitals, hotels, and even on roads.

29. Robotics and Artificial Intelligence (AI) are two separate fields of technology and engineering, but they can be combined to create artificially intelligent robots . Differences between Robotics and AI: Robotics: Robotics involves building robots that can interact with other devices or humans through actuators and data collection sensors Robots can be used to perform autonomous or semi-autonomous tasks Robotics combines with other fields such as mechanical engineering, computer science, and AI Artificial Intelligence: AI is a branch of computer science that creates machines capable of problem-solving and learning similarly to humans AI can function in cell phones, laptops, robots, and other devices AI involves programming intelligence, and it can be used to improve the functioning of robots . In summary, Robotics involves building robots that can perform tasks, while AI involves programming intelligence that can be used to improve the functioning of robots.

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31. APPLICATIONS OF ROBOTICS IN PHARMACEUTICAL INDUSTRIES . Packing drugs in pouches or boxes: Robots can automate the packing of drugs in pouches or boxes, loading products on trays, or stacking boxes on pallets Labeling, filling, and capping of vials: By automating these tasks, pharmaceutical robots can automate up to 80 percent of a pharmacy's medication Filling vials: Robotic technology is used in filling the vials, which includes transferring the components from one container to another . Inspection and preparation for packaging: Automated syringe assembly, inspection, and preparation for packaging is an ideal application for robotics, as it reduces the risk of environmental contamination and contamination generated from human Laboratory automation: Robots can be used for laboratory automation, such as liquid handling robots, which can handle liquids . Pick and place: Robots can perform tasks that involve picking and placing small objects like pills and capsules

32. APPLICATIONS OF ROBOTS PHARMACEUTICAL INDUSTRY R e se a rc h a n d D e v e lo p m e n t (R& D ) Co ntro l Systems Ster i lization a n d Cl e a n Ro o m s Pa c k a gi n g O p erati o ns Flexible Fee d ing 3 Vision S ystems Grin d ing A pplic ations Ster i le Syringe Fi l ling 1 6 J u n e 2 21 28

33. LABORATORY ROBOT IN OPERATIONAL RESEARCH Laboratory robotics is the act of using robots in biology or chemistry labs. For example, pharmaceutical companies employ robots to move biological or chemical samples around to synthesize novel chemical entities or to test pharmaceutical value of existing chemical matter. Advanced laboratory robotics can be used to completely automate the pro c es s o f scie n c e , a s in t h e Ro b o t Scie n ti s t proj e ct. Laboratory processes are suited for robotic automation as the processes are composed of repetitive movements (e.g. pick/place, liquid & solid additions, heating/cooling, mixing, shaking and testing). 33

34. COMBINATORIAL LIBRARY SYNTHESIS Robotics has applications with Combinatorial Chemistry which has great imp a c t o n the p h arma c e u tical in d ust r y. The use of robotics has allowed for the use of much smaller reagent quantities and mass expansion of chemical libraries. The "parallel synthesis" method can be improved upon with automation. The main disadvantage to "parallel-synthesis" is the amount of time it takes to develop a library; automation is typically applied to make this pro c es s m o r e eff i ci e nt. The main types of automation are classified by the type of solid- phase substrates, the methods for adding and removing reagents, and design of reac tion c h a m b e r s . Polymer resins may be used as a substrate for solid-phase. 34

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36. PURIFICATION Simulated distillation, a type of gas chromatography testing method used in the p e troleu m , c a n b e a u tom ated vi a rob o tics. An older method used a system called ORCA (Optimized Robot for Chemical Analysis) was used for the analysis of petroleum samples by s i m u lated dist i llation (S I M D I S ) . ORCA has allowed for shorter analysis times and has reduced maximum te m p e ratur e n e e d e d to elut e c o m p o u n d s. One major advantage of automating purification is the scale at which sep a ration s c a n b e d o n e . Using microprocessors, ion exchange separation can be conducted on a N a n o liter scal e in a sh o r t p e rio d o f time. 36 1 6 J u n e 2 21

37. Robotics has been implemented in liquid-liquid extraction (LLE) to streamline the process of preparing biological samples using 96-well plates. This is an alternative method to solid phase extraction methods and protein precipitation, which has the advantage of being more reproducible and robotic assistance has made LLE comparable in spe e d to s oli d p h as e e x traction. The robotics used for LLE can perform an entire extraction with quantities in the micro liter scale and performing the extraction in as lit t le a s ten min u tes. 1 6 J u n e 2 21 37

38. Pharmaceutical automation refers to the use of automation and robotics in the pharmaceutical industry to improve efficiency, accuracy, and safety. The pharmaceutical industry has benefited from automation in a variety of ways, from design to production, to supply chain operations and tracking and traceability (counterfeit prevention), drug delivery systems, filling, labeling, and capping of vials, inspection and preparation for packaging, laboratory automation, and pick and place. Automation can help pharmaceutical companies to follow stringent regulatory and compliance standards, in addition to reducing operational costs. Automated process techniques can ensure the precise weighing, blending, and tableting of solid dosage forms and filling of liquid pharmaceuticals. Automation technologies help in improving the efficiency of the pharmaceutical development and production by streamlining the processes. The technologies enhance efficiency as robots can easily perform repetitive tasks such as filling and packing at high accuracy and speed compared to human workers. They are also highly accurate and eliminate the possibility of human errors in the weighing, blending, and packaging of pharmaceutical products. Pharmaceutical Automation

39. Role of automation in Pharmaceuticals Automation plays a significant role in solubility, lipophilicity, and permeability assays in drug discovery and development Solubility: Automated liquid handling systems can be used to prepare samples for high-throughput equilibrium solubility determination Automation can be used to perform physical modifications to enhance solubility, such as milling and spray drying Lipophilicity: Automated high-capacity detection systems can be used to analyze the lipophilicity of compounds Automation can be used to perform cytochrome P450 inhibition assays, which are important for evaluating the metabolic stability of compounds Permeability: Automation can be used to perform permeability assays, such as the Parallel Artificial Membrane Permeation Assay (PAMPA), which can be used to evaluate the passive membrane permeability of compounds . Automated liquid handling systems can be used to prepare samples for permeability assays .

40. Liquid handling: Automated liquid handling systems can perform precise and accurate liquid transfers, reducing the risk of human error and improving the reproducibility of experiments . High capacity detection: Automated detection systems can analyze large numbers of samples quickly and accurately, allowing researchers to screen a large number of compounds more rapidly . Data processing and reporting: Automated data processing and reporting systems can analyze and report data quickly and accurately, allowing researchers to make informed decisions more quickly Automation can help to streamline the drug discovery process by reducing the time and cost required to perform experiments, improving the accuracy and reproducibility of results, and allowing researchers to screen a larger number of compounds more quickly. Laboratory automation: Automation can be used to improve the efficiency and accuracy of laboratory tasks, such as liquid handling, sample preparation, and data analysi

41. Some examples of automated systems used in pharmaceutical manufacturing: Automated pill bottle assembly, labeling, and packaging systems Automated syringe assembly, inspection, and preparation for packaging Automatic drug / medication dispensing Automatic syringe labeling systems Aseptic monoblock dispensing, filling, and capping system Aseptic syringe or vial dispensing, filling, and capping system Clean room robot solutions for use in a variety of automated systems at hospitals, pharmacies, lab room settings, and more Prescription delivery device assembly Robotic cartoning , case packing, and palletizing systems

42. Automation plays a significant role in the characterization of dosage forms, particularly in dissolution testing of solid oral dosage forms . Here are some ways automation helps in the characterization of dosage forms: Dissolution testing: Automation can be used to perform dissolution testing of solid oral dosage forms, which is a critical step in the development of new products and in quality control 1 2. Sample preparation: Automation can be used to prepare samples for analysis, improving the accuracy and reproducibility of results 3. Data processing and reporting: Automated data processing and reporting systems can analyze and report data quickly and accurately, allowing researchers to make informed decisions more quickly

43. Good Automated Manufacturing Practice (GAMP) is a set of guidelines for manufacturers and users of automated systems in the pharmaceutical industry The guidelines provide a structured approach for the validation of automated systems and ensure that pharmaceutical products have the required quality The International Society for Pharmaceutical Engineering (ISPE) has published a series of good practice guides for the industry on several topics involved in drug manufacturing, including GAMP . Here are some key principles of GAMP: Quality must be built into each stage of the manufacturing process, rather than tested into a batch of product GAMP covers all aspects of production, including facilities, equipment, materials acquisition, and staff hygiene GAMP guidelines are used heavily by the pharmaceutical industry to ensure that drugs are manufactured with the required quality GAMP makes quality testing an integral part of each stage of manufacturing, including facilities, equipment, materials acquisition, and staff hygiene GAMP provides a cost-effective framework of good practice to ensure that computerized systems are fit for intended use GAMP is a set of guidelines that helps pharmaceutical companies comply with regulatory standards by providing a structured approach for the validation of automated systems and ensuring that pharmaceutical products have the required quality. By following GAMP guidelines, companies working in regulated industries can ensure automated systems quality and make it easier to pass audits and government inspections. .

44. TYPES OF AUTOMATION TYPES OF AUTOMATION 1.Feedbac k c o ntrol 2.Sequential control & logical sequence control 3 . C omp u ter control ROBOTS USED IN PHARMACEUTICAL INDUSTRY Pha r mac e utic a l Containe r Repl a cem e n t Robot Cylindrica l Ro b o t f o r High Thro u gh p u t S cr e ening Six-Axis Robots suit Class 1 Clean Room Applications Spa c e S a vin g Ceilin g Mou n ted Robot Metal Detector Targets Pharmaceutical Industry 27

45. A DVANTAGES OF ROBOTICS One of the advantages to automation faster processing, but it is not n e c e s s aril y fas t e r th a n a hum a n o p erat o r. Repeatability and reproducibility are improved as automated systems as less likely to have variances in reagent quantities and less likely to h a v e v a rianc e s in re a ctio n c o n d itions. Typically productivity is increased since human constraints, such as time c o nst r aints , ar e n o lo n g e r a f a c tor. Efficiency is generally improved as robots can work continuously and reduce the amount of reagents used to perform a reaction. Also there is a r e d u ction in material w a s t e. Automation can also establish safer working environments since h a z a rd o u s c o m p o u n d s d o n o t h a v e to b e h a n d le d . Additionally automation allows staff to focus on other tasks that are n o t rep e tit i v e . 1 6 J u n e 2 21 34

46. DISADVANTAGES OF ROBOTICS Typically the costs of a single synthesis or sample assessment are expensive to set up and startup cost for automation can be expensive. Many techniques have not been developed for automation yet. Additionally there is difficultly automating instances where visual analysis, recognition, or comparison is required such as color changes. This also leads to the analysis being limited by available sensory inputs. One potential disadvantage is an increases job shortage as automation may replace staff members who do tasks easily replicated by a robot. Some systems require the use of programming languages such as C++ or Visual Basic to run more complicated tasks. 35

47. CURRENT CHALLENGES/ FUTURE ASPECT In medical device manufacturing, robotics plays an active role in assembly. The manufacturing process is highly regulated and must be approved by the Food a n d Drug A d minist r atio n ( F D A ) . M a n u fact u re s us e r o b otics to r e d u c e c o s t . Robotics performs important tasks in surgical procedures. Robots are used for delivery of radiation and for proton therapy. The goal is to administer the smallest dose of radiation as possible to the precise location. Robots are very precise, positioning equipment and patients accurately in three- di m e n sion a l sp a c e . Robots are loading and unloading injection moulding machines, assembling medical devices and polishing implants. In pharmaceutical production, robots handle bottles in the cell culture process, loading and unloading autoclaves and packaging machines, as well as de- nesting syringe tubs. Robotics has a certain future in laboratory, life science and pharmaceutical a p plic a tions. T h er e is in c rease d a c tivity fo r b e n c h - to p rob o tics performing various protocols. These stations are reprogrammable and many are complex. Ro b o tics is essentia l to mod e r n scientifi c . 36

48. Computational Fluid Dynamics F luid dynamics , deals with the effects of forces on fluid motion. With the evolution in computer technology, a branch of fluid dynamics called computational fluid dynamics (CFD) has become a powerful and cost- effective tool for simulating real fluid flow. The explanations for many natural phenomena, such as river flows, ocean waves, wind currents, functioning of the human body (e.g. cardiovascular and pulmonary system), lie in the field of fluid mechanics. Fluid mechanics has, above all, a great importance in development and performance optimization of complex engineering systems, such as airplanes, ships, cars. Recent results have announced the importance and possible applications of fluid mechanics in the fi eld of biomedicine. For example, some of the procedures used in treatment of blood vessel obstruction (e.g. stenting, balloon angioplasty, in situ drug delivery for unclotting , bypass surgery, etc.) have statistically significant failure rates, which indicates a need for a patient- specific approach and detailed study of fluid dynamics before and after intervention.

49. CFD is an area of fluid dynamics that deals with finding numerical solutions to equations describing the fluid flow to obtain a numerical description of the entire flow field. CFD is a very realistic flow simulation that can quantify the mixing and also the shear stress in product. CFD offers significant time and cost savings, as well as comprehensive information about fluid flow in the investigated system, whereas experimental methods are limited to measurements at certain locations in the system. Moreover, numerical simulations allow testing of the system under conditions in which it is not possible or is difficult to perform experimental tests CFD is based on the analysis of fluid flow in a large number of points (elements/volumes) in the system, which are further connected in a numerical grid/mesh. CFD software packages are based on highly complex nonlinear mathematical expressions derived from fundamental equations of fluid flow, heat, and mass transfer, and can be solved by complex algorithms built into the program.

50. APPLICATION OF CFD IN PHARMACEUTICS The application of CFD to a few key unit operations and processes in the pharmaceutical industry was described as follows: CFD f o r mixi n g. CFD f o r solid s ha n dlin g . CF D fo r se p arati o n. CFD f o r dry e r s . CFD f o r p a c k a g in g . CFD for energy generation and energy-transfer devices. 50

51. CFD FOR MIXING: CFD methods can be applied to examine the performance of static mixers and to predict the degree of mixing achieved, thus indicating whether more mixing elements are required 51 Modeling of mixing processes : CFD provides a method to link the process and fluid flow information, making it a powerful tool for the modeling of mixing processes Optimization of mixing process : CFD can be used to optimize the mixing process, resulting in improved overall mixing performance and product uniformity, increased product and process quality, enhanced vessel performance, increased throughput, and reduced waste . Characterization of mixing and energy dissipation efficiency : CFD has traditionally been used at a basic level to characterize mixing and energy dissipation efficiency . Troubleshooting : CFD can be used to troubleshoot mixing problems and identify the root cause of issues

52. 42 Modeling of mixing processes : CFD provides a method to link the process and fluid flow information, making it a powerful tool for the modeling of mixing processes . Optimization of mixing process : CFD can be used to optimize the mixing process, resulting in improved overall mixing performance and product uniformity, increased product and process quality, enhanced vessel performance, increased throughput, and reduced waste . Characterization of mixing and energy dissipation efficiency : CFD has traditionally been used at a basic level to characterize mixing and energy dissipation efficiency . Troubleshooting : CFD can be used to troubleshoot mixing problems and identify the root cause of issues

53. CFD FOR SEPARATION: CFD techniques are used for analyzing separation devices such as cyclones and scrubbers. The following example incorporates CFD methods to optimize and predict p e r f orm a n c e o f a n e x is ting c y cl o n e d e sign. CFD solutions depict particle paths for various particle sizes. In this example, CFD techniques were used to perform what-if analysis for o p timization o f the d e s i g n . T h e p e r f orm a n c e c o m p ut e d with CF D cl o sely mat c h e d th a t o b serve d in p h y s i c a l test i n g w h erei n 9 % of 10-m particles were removed, but only 10% of 1-m particles were separated from the air stream. 43

54. CFD FOR DRYERS: We use d CFD t o an a ly z e the p e r f orman c e o f a n in d ust r ial spray c h a n g e s to the dry e r. T h is st r at e g y minimi z e s the ri s k of lost profi t d u rin g c h a n g e o v e r, especially if the improvement does n o t m a terializ e . CFD was a p plie d to ex a mine c o nfigur a tion ch a n g es , th u s minimi z ing ri s k a n d av o iding u n n e c e s s ar y d o w n time d u rin g test i ng sho w s the v e lo c ity dist rib u tion ( s k e w e d flow). dryer before making major structural  CFD models were applied to T h is f l o w is a resul t o f u n e ven pressur e dist r ib u tion in t h e air disp e r s ing h ea d. d e termi n e o p timum e q ui p m e nt c o nfigur a tion an d pro c es s sett i n g s. CFD r esult s provi d e d the n e c e s s ary c o nfide n c e th a t the pro p osed m o dific a tio n s w o ul d w o r k s o c a p ital e q ui p me n t w o ul d b e ord e re d and fiel d - test i n g c o ul d b e sch e d u led. 44

55. CFD FOR PACKAGING: CFD can be applied to conduct virtual experiments before changes are made to the filling lines or to the package geometry. This method allows a wide range of conditions to be tested and leads to an optimized filling process, depicts the filling of a container. The figures shown are typical of solution results that are used to optimize filling processes to increase throughput and reduce foaming. (a)filling process, liquid surface location, strong splash; (b) filling process, liquid surface location, no sp l a s h. 55 1 6 J u n e 2 21

56. C F D F O R E N ER G Y G E N E R A TIO N A N D E N ER G Y - TR A N SF E R DEVICES: CFD techniques can be applied to analyze thermal and flow fields within suc h d e vi c es. CFD modeling methods also can be applied to gain insight into flame characteristics. Maintaining flame stability and burner efficiency is very critical to the pro p e r fu n ctio n ing o f a pro c es s h e at e r , p o w e r pl a nt , o r furn a c e . Flame le n gt h , sh a p e , a n d siz e c a n influ e n c e the pr o c e s s . If the flame is too long, then it can impinge on critical regions of the a p p a ratu s a n d c a us e th e rma l d a ma g e. If the flam e i s too s h o rt , then it may w e a r o u t the b u rne r tip. Replacing the burner or associated apparatus results in downtime and loss o f p rod u c t rev e n u e. 56

57. ADVANTAGES OF CFD A gre a t time red u ctio n a n d c o s t red u ctio n in ne w d e s i g n s. There is a possibility to analyze different problem whose experiments ar e v e r y difficul t a n d d a n g er o us. The CFD techniques offer the capacity of studying system under c o n d itions o v e r its limit s . The level of detail is practically unlimited. T h e pr o d u c t get s a d d e d v a lu e . The possibility to generate different graph permits to understand the feat u re s o f the result . T h is e n c o ura g e s b u yi n g a n e w pro d u c t. H i - T e c h CFD i s a c o m p ut e r aid e d e n gi n e e rin g c o m p a n y w h ich provides total solutions to engineering problems in the field of Co m p ut a tion a l Fluid D y n ami c s (CFD),Co m p u tatio n al Electromagnetic, Computational Structural Mechanics, Dynamics and Controls. 47

58. DISADVANTAGES OF CFD Accuracy in the result is doubted i.e. in certain situations we will not o b tain succ ess f u l r esult. It is necessary to simplify mathematically the phenomenon to facilitate calculus. If the simplification has been good the result will be more accurate. There are several incomplete models to describe the turbulence, multiphase phenomenon, and other difficult problems. Untrained user of CFD has the tendency to believe that the output of the p c is al w ay s true 48

59. CURRENT CHALLENGES/ FUTURE ASPECT The integration of CFD methods can shorten product-process development cycles, optimize existing processes, reduce energy requirements, and lead to the efficient design of new products and processes. Unit operations in the pharmaceutical industry handle large amounts of fluid. As a result, small increments in efficiency, such as those created by implementing CFD sol u tio n s , c a n le a d to s ig n ific a n t pr o d u c t cos t s a vi n gs. Key processes in the pharmaceutical industry can be improved with CFD techniques. The aerospace and automobile industries already have integrated CFD methods into their desig n p roce s s . T he chemical process and the pharmaceutical industries now are beginning to integrate this technology. The full potential for process improvements using CFD solutions is yet to be realized. 49

60. Application of CFD in pharmaceutical technology CFD has been recognized as a promising tool for the analysis and optimization of various pharmaceutical unit operations, process equipment, drug delivery devices, quality control equipment, etc. Inhaler development Pressurized metered- dose inhalers (MDIs) have been extensively used in the treatment of respiratory diseases, such as asthma, cystic fibrosis, emphysema, etc. However, MDIs have certain disadvantages, such as the need for coordination of MDI actuation and patient inhalation, high oropharyngeal drug deposition, the absence of a dose counter, etc. These disadvantages, together with environmental concerns regarding the use of chlorofluorocarbon (CFC) as propellants, have led to increased research efforts directed towards development of alternative devices, such as dry powder inhalers (DPIs). DPI performance seems to be most dependent on the air flow through the device, such as on the patient’s inspiration, in order to achieve sufficient turbulence to fluidize the powder bed. Therefore, DPIs represent interesting candidates for application of CFD in the development process

61. Two commercial DPIs with different geometries were used in the study: the Aerolizer ® ( Plastiape S.p.A., Italy) and the Handihaler ® (Boehringer Ingelheim Inc., USA). Distinct differences in velocity profiles and particle trajectories ( Figure 7.8 ) within the two inhalers were observed. It was found that fluid flow within the Aerolizer ® promotes particle collisions with the inhaler wall and swirling particle motion inside the mouthpiece. However, collisions are less frequent in the Handihaler and particles are accelerated and directed towards the inhaler wall and then towards the inhaler exit, without any swirling motion

62. Dissolution apparatus hydrodynamics Knowledge of the hydrodynamic conditions specific to the selected dissolution apparatus is important, since small differences in hydrodynamic conditions can result in misleading conclusions CFD can be successfully applied for simulation, analysis, and gaining insight into the hydrodynamic conditions present in different dissolution aparatuses . The USP paddle apparatus is the most widely used dissolution apparatus with a relatively simple design, but there are still problems related to the reproducibility of the results and development of an in vitro- in vivo correlation. This can be partly attributed to the complex hydrodynamics, which are not well understood and seem to be variable at different locations within the vessel. It was shown that small differences in tablet position within the vessel can affect the hydrodynamics, leading to pronounced differences in dissolution rates McCarthy et al. (2004) applied CFD to simulate the influence of paddle rotational speed on hydrodynamics in a dissolution vessel. It was found that the magnitude of both axial and tangential components of velocity increased linearly with increase in paddle rotational speed from 25 to 150 rpm.

63. One of the most important factors affecting the efficiency of the fluid bed process is the air flow and its distribution within the processing chamber. Depypere et al. (2004) used CFD to investigate the effects of the air distributor design and the upstream air supply system on the airflow in a top- spray fluid bed processor. It was shown that the velocity of the air injected via the nozzle and position of the draft tube in the Wurster granulator can affect fluid and particle dynamics. Fluidized bed process simulation

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