AI

1. ARTIFICIAL INTELLIGENCE (AI),
ROBOTICS AND COMPUTATIONAL
FLUID DYNAMICS (CFD)
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2021
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2. CONTENTS
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General overview
Pharmaceutical Automation
Pharmaceutical applications
Advantages and Disadvantages
Current Challenges and FutureDirections

3. INTRODUCTION TO ARTIFICIAL INTELLIGENCE
(AI)
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According tothefather ofArtificial Intelligence, John McCarthy, it is “The scienceand
engineeringofmakingintelligentmachines, especially intelligent computer programs”.
Also, intelligence distinguish us fromeverything in theworld.As it has theability to
understand, apply knowledge.
Also, improveskills thatplayedasignificantroleinourevolution.WecandefineAI as thearea
of computer science.
Further,theydealwiththewaysinwhichcomputerscanbemade.As they madetoperform
cognitive functions ascribedtohumans.

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5. Artificial Intelligence (AI) refers totheability of acomputer or acomputer-
enabledroboticsystemtoprocessinformationand produceoutcomesinamanner
similar to the thought process of humans in learning, decision making and
solving problems.
By extension, the goal of AI systems is to develop systems capable of
tackingcomplexproblemsin wayssimilar tohumanlogic andreasoning.
 Artificial intelligence – AI – is getting increasingly sophisticated at doing
whathumans do,albeitmoreefficiently, morequickly,88 andmorecheaply.
 While AI and robotics are becoming a natural part of our everyday
lives, theirpotentialwithinhealthcareis vast. 5

6.  Artificial Intelligenceis a new electronicmachine thatstoreslarge amountof informationandprocessit at
very highspeed.
 Thecomputeris interrogatedbyahumanviaa teletypeIt passesif thehumancannottell if thereis a
computer orhumanatthe otherend.
 Theability tosolvetheproblems.
 It is the scienceand engineering ofmakingintelligentmachines,especially intelligentcomputerprograms.
 It is relatedtothe similartaskof usingcomputerstounderstandhumanintelligence.
 Brief historyofAI:
 1941-First electroniccomputer(technologyfinally available)
 1956- Termartificial intellienceintroduced.
 1960s-Checkers–playing programthatwasabletoplay withopponents.
 1980s- Quality control system.
 2000-First sophisticatedwalkingrobot.
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7. OVERVIEW OF AI :
Sincetheinventionofcomputersormachines,theircapabilityto performvarious
taskswentongrowing exponentially.
Humans have developed the power of computer systems in terms of their diverse
workingdomains,theirincreasingspeed,andreducing sizewithrespecttotime.
A branch of Computer Science named Artificial Intelligence pursues creating the
computersormachinesasintelligentashumanbeings.
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8. PHILOSOPHY OFAI
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Whileexploitingthepowerofthecomputersystems,thecuriosityof human,leadhimto
wonder,“Can amachinethinkandbehavelike humans do?”
Thus, the development of AI started with the intention of creating similar
intelligenceinmachinesthatwefindandregardhighin humans.
Goals ofAI
To CreateExpertSystems.
To ImplementHumanIntelligencein Machines.

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10. PROGRAMMING WITHOUT AND WITH AI
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11. WHAT IS AI TECHNIQUE?
• In thereal world, theknowledge has someunwelcomed properties:
Its volumeis huge, next tounimaginable.
It is not well-organized orwell-formatted.
It keeps changing constantly.
AI Technique is a mannerto organize anduse theknowledge efficiently in such a way
that: It shouldbeperceivablebythepeople whoprovide it.
It should beeasily modifiabletocorrect errors.
It should beuseful in manysituationsthoughit is incomplete
or inaccurate.
AI techniqueselevatethespeedofexecution ofthecomplex
program it is equipped with.
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13. ADVANTAGES OF AI :
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a. Error Reduction:
Weuseartificialintelligenceinmostofthecases.As thishelpsusin reducingtherisk.
Also, increasesthechanceof reachingaccuracywiththegreater degreeof
precision.
b. Difficult Exploration:
Inmining,weuseartificialintelligenceandscienceofrobotics.Also, otherfuel
explorationprocesses.
Moreover,weusecomplexmachinesforexploringtheocean.Hence,
overcomingtheoceanlimitation.

14. c. Daily Application:
As weknowthatcomputedmethodsandlearninghavebecomecommonplacein daily life.
Financial institutionsandbankinginstitutionsarewidely usingAI. Thatis toorganizeandmanage
data.
Also, AI is usedinthedetectionoffraudusersinasmartcardbasedsystem.
d. Digital Assistants:
“Avatars” areusedbyhighly advancedorganizations.That aredigital
assistants.
Also, they caninteractwiththeusers. Hence. Theyaresaving human needs of resources.
As wecansaythattheemotionsareassociatedwithmood.
Thatthey cancloudjudgmentandaffecthumanefficiency. Moreover, completely ruledoutfor
machineintelligence.
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15. e. Nobreaks:
Machinesdonotrequirefrequentbreaksandrefreshmentsforhumans.As machinesare
programmedforlonghours.
Also, they cancontinuously performwithoutgettingbored.
f. IncreaseWork Efficiency:
Foraparticularrepetitivetask,AI-poweredmachinesaregreatwithamazing efficiency.
Bestis theyremovehumanerrorsfromtheirtaskstoachieveaccurate
results.
g. Reducecostoftraining andoperation:
DeepLearningandneuralnetworksalgorithmsusedinAI tolearnnewthings like humans
do.
Also, thiswaytheyeliminatetheneedtowritenewcodeeverytime.
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16. DISADVANTAGES OF ARTIFICIAL INTELLIGENCE:
a. HighCost:
Its creationrequireshugecostsastheyarevery complexmachines.
Also, repairandmaintenancerequirehugecosts.
b. NoReplicating Humans:
As intelligenceis believedtobeagift of nature.
An ethical argument continues, whetherhumanintelligence is tobe
replicatedornot.
c. Lesser Jobs:
As weareawarethatmachinesdoroutineandrepeatabletasksmuchbetterthanhumans.
Moreover,machinesareusedofinsteadofhumans.As toincreasetheir profitabilityin
businesses.
d. Lack of Personal Connections:
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17. Wecan’t relytoomuchonthesemachinesforeducational oversights.
Thathurtlearnersmorethanhelp.
e. Addiction:
As werelyonmachinestomakeeverydaytasksmoreefficientweuse
machines.
f. EfficientDecisionMaking:
As weknowcomputersaregettingsmartereveryday.
Also,theyaredemonstratingnotonlyanabilitytolearnbuttoteachother
computers.
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18. APPLICATIONS OF AI IN PHARMACEUTICALS
AI havevariousapplicationsinhealthcareandpharmacywhichareas
follows:
Disease Identification
Personalizetreartment
Drug Discovery/Manufacturing
Clinical Trial Research
Radiology andRadiotherapy
Smartelectronichealthrecord 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
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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
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27. CURRENT CHALLENGES/ FUTURE ASPECT
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ManybigPharmaceuticalcompaniesbeganinvestinginAI inordertodevelopbetter
diagnosticsorbiomarkers,toidentifydrugtargetsandtodesignnewdrugsandproducts.
MerckpartnershipwithNumerategeneratingnovelsmallmoleculecardiovascular
diseasetarget.inMarch2012 focusingondrugleadsforunnamed
InDecember,2016PfizerandIBMannouncedpartnershiptoacceleratedrugdiscoveryin
immunooncology.

28. INTRODUCTION TO ROBOTICS
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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

33. APPLICATIONS OF ROBOTS
PHARMACEUTICAL INDUSTRY
 ResearchandDevelopment(R&D)
 ControlSystems
 SterilizationandCleanRooms
 PackagingOperations
 Flexible Feeding3
 VisionSystems
 GrindingApplications
 SterileSyringeFilling
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34. LABORATORY ROBOT IN OPERATIONAL RESEARCH
 Laboratoryroboticsistheactofusingrobotsinbiologyorchemistrylabs.
 Forexample,pharmaceuticalcompaniesemployrobotstomovebiologicalorchemicalsamplesaroundto
synthesizenovelchemicalentitiesortotestpharmaceuticalvalueofexisting chemicalmatter
.
 Advancedlaboratoryroboticscanbeusedtocompletelyautomatetheprocessofscience, asin theRobotScientist
project.
 Laboratoryprocessesaresuitedforroboticautomationastheprocessesarecomposedofrepetitivemovements(e.g.
pick/place,liquid&solid additions,heating/cooling,mixing,shakingandtesting).
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35. COMBINATORIAL LIBRARY SYNTHESIS
Robotics hasapplications withCombinatorialChemistrywhichhasgreat impact onthe
pharmaceutical industry.
Theuseof roboticshasallowedfor theuseofmuchsmallerreagent
quantitiesandmassexpansionof chemical libraries.
The"parallel synthesis"methodcanbeimproveduponwithautomation.
Themaindisadvantageto"parallel-synthesis"is theamountoftimeit takestodevelopa
library;automationis typicallyappliedtomakethis processmoreefficient.
Themaintypesofautomationareclassifiedbythetypeofsolid-phase substrates,the
methodsforaddingandremovingreagents,anddesignof reactionchambers.
Polymerresinsmaybeusedasasubstrateforsolid-phase.
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37. PURIFICATION
Simulateddistillation,atypeofgaschromatographytestingmethodusedin
thepetroleum, canbeautomatedviarobotics.
 AnoldermethodusedasystemcalledORCA (OptimizedRobotfor
Chemical Analysis) wasusedfortheanalysis ofpetroleumsamplesby
simulateddistillation(SIMDIS).
 ORCA hasallowedforshorteranalysistimesandhasreducedmaximum
temperatureneededtoelutecompounds.
 Onemajoradvantageofautomatingpurificationis thescaleatwhich
separationscanbedone.
 Usingmicroprocessors,ionexchangeseparationcanbeconductedona
Nanoliterscalein ashortperiodof time.
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38.  Roboticshasbeenimplementedinliquid-liquidextraction(LLE) tostreamlinetheprocessof
preparingbiologicalsamplesusing96-wellplates.
 This is analternativemethodtosolidphaseextractionmethodsandproteinprecipitation,which
hastheadvantageofbeingmorereproducibleandroboticassistancehasmadeLLE comparablein
speedtosolidphaseextraction.
 TheroboticsusedforLLE canperformanentireextractionwith quantitiesinthemicroliterscale
andperformingtheextractionin aslittleastenminutes.
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39.  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

40. 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
.

41. 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

42. 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

43. Automation plays a significant role in the characterization of dosage forms, particularly in dissolution testing of
solid oral dosage forms
1.. 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 control1
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

44. 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:
1.Quality must be built into each stage of the manufacturing process, rather than tested into a batch of
product
2.GAMP covers all aspects of production, including facilities, equipment, materials acquisition, and staff
hygiene
3.GAMP guidelines are used heavily by the pharmaceutical industry to ensure that drugs are manufactured
with the required quality
4.GAMP makes quality testing an integral part of each stage of manufacturing, including facilities, equipment,
materials acquisition, and staff hygiene
5.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.

45. TYPES OF AUTOMATION TYPES OF AUTOMATION
 1.Feedbackcontrol
 2.Sequentialcontrol&logicalsequencecontrol
 3.Computercontrol
ROBOTS USED IN PHARMACEUTICAL INDUSTRY
 Pharmaceutical ContainerReplacementRobot
 Cylindrical RobotforHighThroughputScreening
 Six-Axis RobotssuitClass1CleanRoomApplications
 SpaceSavingCeiling MountedRobot
 MetalDetectorTargetsPharmaceuticalIndustry
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46. ADVANTAGES OF ROBOTICS
 Oneoftheadvantagestoautomationfasterprocessing,butit is not
necessarilyfasterthanahumanoperator.
 Repeatability andreproducibility areimproved as automatedsystems
aslesslikely tohavevariancesin reagentquantitiesandless likely to
havevariancesinreactionconditions.
 Typically productivityis increasedsince humanconstraints,suchas
timeconstraints,arenolongerafactor.
 Efficiency is generally improved as robots can work continuously and
reducetheamountofreagentsusedtoperformareaction.Also thereis
areductioninmaterialwaste.
 Automationcanalsoestablishsaferworkingenvironmentssince
hazardouscompoundsdonothavetobehandled.
 Additionallyautomationallowsstafftofocusonothertasksthatare
notrepetitive.
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47. DISADVANTAGES OF ROBOTICS
Typically thecostsofasinglesynthesisorsampleassessmentare expensivetosetupandstartup
costforautomationcanbeexpensive.
Manytechniqueshavenotbeendeveloped forautomationyet.
Additionallythereis difficultlyautomatinginstanceswherevisual analysis, recognition,or
comparisonis requiredsuchascolorchanges.
This alsoleadstotheanalysisbeinglimitedbyavailablesensoryinputs.
Onepotentialdisadvantageis anincreasesjobshortageasautomationmayreplacestaffmembers
whodotaskseasily replicatedbyarobot.
Somesystemsrequiretheuseofprogramminglanguages suchasC++ orVisual Basic torun
morecomplicated tasks.
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48. CURRENT CHALLENGES/
FUTURE ASPECT
 In medicaldevice manufacturing, roboticsplaysanactive rolein assembly.The manufacturing
processis highlyregulated andmustbeapprovedby theFood andDrug Administration(FDA).
Manufacturesuseroboticstoreducecost. Robotics performsimportanttasksin surgical procedures.
 Robotsareusedfordelivery ofradiationandforprotontherapy.Thegoalis to administerthesmallest
doseofradiationaspossibletotheprecise location. Robotsareveryprecise,positioningequipment
andpatientsaccuratelyinthree-dimensional space.
 Robotsareloadingandunloadinginjectionmouldingmachines,assembling medicaldevicesand
polishingimplants.Inpharmaceuticalproduction,robots handlebottlesinthecellcultureprocess,
loadingandunloadingautoclavesandpackagingmachines,aswell asde-nestingsyringetubs.
 Roboticshasacertainfutureinlaboratory,life scienceandpharmaceuticalapplications.Thereis
increasedactivity forbench-toproboticsperformingvariousprotocols.Thesestationsare
reprogrammableandmanyarecomplex.Roboticsis essential tomodernscientific .
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49. Computational Fluid Dynamics
• Fluid 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.

50. • 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.

51. APPLICATION OF CFD IN
PHARMACEUTICS
TheapplicationofCFD toafewkeyunitoperationsandprocessesin
thepharmaceuticalindustrywasdescribedasfollows:
 CFD formixing.
 CFD forsolidshandling.
 CFD forseparation.
 CFD fordryers.
 CFD forpackaging.
 CFD forenergygenerationandenergy-transferdevices.
51

52.  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
52
•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. 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

54.  CFD FOR SEPARATION:
 CFD techniquesareusedforanalyzing separationdevicessuchascyclones andscrubbers.
 Thefollowing exampleincorporatesCFD methodstooptimizeandpredictperformanceofanexistingcyclonedesign.
 CFD solutionsdepictparticlepathsforvariousparticlesizes.
 Inthisexample,CFD techniqueswereusedtoperformwhat-ifanalysisforoptimization ofthedesign.
 TheperformancecomputedwithCFD closely
matchedthatobservedinphysical testingwherein90% of10-mparticleswereremoved,butonly
10%
of1-mparticleswereseparatedfromtheairstream.
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55.  CFD FOR DRYERS:
 WeusedCFD toanalyzethe
performanceofanindustrial spray
changestothedryer.
 This strategyminimizestheriskof
lostprofitduringchangeover,
especially if theimprovementdoes
notmaterialize.
 CFD wasappliedtoexamine
configurationchanges, thus
minimizing riskandavoiding
unnecessarydowntimeduringtesting
showsthevelocity distribution
(skewedflow).
dryerbeforemakingmajorstructural CFD modelswereappliedto
 This flowis aresultof uneven
pressuredistribution in theair
dispersinghead.
determineoptimumequipment
configurationandprocesssettings.
 CFD resultsprovidedthenecessary
confidencethattheproposed
modificationswouldworksocapital
equipmentwouldbeorderedand
field- testingcouldbescheduled.
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56.  CFD FOR PACKAGING:
 CFD canbeappliedtoconductvirtualexperimentsbeforechangesare
madetothefilling lines ortothepackagegeometry.
 This methodallowsawiderangeofconditionstobetestedandleads
toanoptimizedfilling process,depictsthefilling ofacontainer
.
 Thefiguresshownaretypicalofsolutionresultsthatareusedto
optimizefilling processestoincreasethroughputandreducefoaming.
(a)fillingprocess,liquidsurfacelocation,strong
splash;(b)filling process,liquidsurfacelocation,
nosplash.
56
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57.  CFD FOR ENERGY GENERATIONAND ENERGY- TRANSFER
DEVICES:
 CFD techniquescanbeappliedtoanalyzethermalandflowfieldswithin
suchdevices.
 CFD modelingmethodsalsocanbeappliedtogaininsightintoflame
characteristics.
 Maintainingflamestability andburnerefficiency is verycritical tothe
properfunctioning of aprocessheater, power plant, or furnace. Flame
length, shape, andsizecaninfluencetheprocess.
 If theflameis toolong,thenit canimpingeoncriticalregionsofthe
apparatusandcausethermal damage.
 If theflameistooshort,thenitmaywearouttheburnertip.
 Replacingtheburnerorassociatedapparatusresultsin downtimeandloss
ofproductrevenue.
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58. ADVANTAGES OF CFD
 A greattimereductionandcostreductioninnewdesigns.
 Thereisapossibilitytoanalyzedifferentproblemwhoseexperiments
areverydifficultanddangerous.
 TheCFD techniquesofferthecapacityofstudyingsystemunder
conditionsoveritslimits.
 Thelevel ofdetailis practically unlimited.
 Theproductgetsaddedvalue.
 Thepossibilitytogeneratedifferentgraphpermitstounderstandthe
featuresoftheresult. This encouragesbuyinganewproduct.
 Hi-TechCFD isacomputeraidedengineeringcompany which
providestotalsolutionstoengineeringproblemsinthefieldof
Computational Fluid Dynamics (CFD),Computational
Electromagnetic,ComputationalStructuralMechanics,Dynamics and
Controls.
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59. DISADVANTAGES OF CFD
 Accuracyintheresultis doubtedi.e.incertainsituationswewill not
obtainsuccessful result.
 It is necessarytosimplifymathematically thephenomenontofacilitate
calculus.If thesimplificationhasbeengoodtheresultwill bemore
accurate.
 Thereareseveralincompletemodelstodescribetheturbulence,
multiphasephenomenon,andotherdifficultproblems.
 UntraineduserofCFD hasthetendencytobelievethattheoutputof
thepcis alwaystrue
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60. CURRENT CHALLENGES/ FUTURE ASPECT
 TheintegrationofCFD methodscanshortenproduct-processdevelopmentcycles,optimizeexistingprocesses,
reduceenergyrequirements,andleadtotheefficientdesignofnewproductsandprocesses.
 Unitoperationsinthepharmaceuticalindustry handlelarge amountsoffluid.As a result,smallincrementsin
efficiency,suchasthosecreatedby implementingCFD solutions,canleadtosignificantproductcostsavings.
 KeyprocessesinthepharmaceuticalindustrycanbeimprovedwithCFD
techniques.
 The aerospaceandautomobileindustriesalreadyhaveintegratedCFD methodsintotheirdesignprocess.
 Thechemicalprocessandthepharmaceuticalindustriesnowarebeginningto
integratethistechnology.
 ThefullpotentialforprocessimprovementsusingCFD solutionsisyettoberealized.
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61. 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

62. • 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

63. • 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.

64. • 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

65. REFERENCES:
 https://www.slideshare.net/ChandrakantKharude/artificialintelligencer
oboticsandcomputationalfluiddynamics-190207065757 Assessed Date:
14/06/2021
 https://www.slideshare.net/PrasathP13/artificial-intelligence-
138582081AssessedDate:14/06/2021
 https://www.slideshare.net/PrashantChaurasiya5/artificial-intligence-
and-robotics-pptAssessedDate:14/06/2021
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2021
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