【NishithDesai】医疗保健中的人工智能-在印度探索监管前沿-2025.3

MUMBAISILICONVALLEYBENGALURUSINGAPORENEWDELHINEWYORKGIFTCITY

Research

Artificial

IntelligenceinHealthcare

NavigatingRegulatoryFrontiersinIndia

March2025

©NishithDesaiAssociates2025

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©NishithDesaiAssociates2025

Research

Artificial

IntelligenceinHealthcare

NavigatingRegulatoryFrontiersinIndia

March2025

DMSCode:119795.2

©NishithDesaiAssociates2025concierge@

©NishithDesaiAssociates2025

Rankedasthe‘MostInnovativeIndianLawFirm’intheprestigiousFTInnovativeLawyers

AsiaPacificAwardsformultipleyears.Alsorankedamongstthe‘MostInnovativeAsiaPacificLawFirm’intheseeliteFinancialTimesInnovationrankings.

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Acknowledgements

UttaraJhaveri

uttara.jhaveri@

UttaraisamemberofthePharmaceutical,Healthcare,MedicalDevice,andDigitalHealthTeamatNishithDesaiAssociates.SheholdsanLLM(NationalandGlobalHealth)fromGeorgetownUniversityLawCenter.Shehasadvisedpharmaceuticalcompanies,medicalprofessionals,andmedicaldevicecompaniesonregulatoryandcompliancemattersandhasexperienceinlitigation.

TanyaKukade

tanya.kukade@

TanyaisaseniormemberinthePharmaceutical,Healthcare,MedicalDeviceandDigitalHealthTeamatNishithDesaiAssociates.Additionally,sheisalsoanintegralpartoftheMake-in-Indiapractice

atNishithDesaiAssociates.

Shehasadvisednumerousmultinationalpharmaceuticalandmedicaldevicecompaniesonregulatoryaspectsooflicensing,priceregulation,import,compliances,aswellasintellectualpropertymatters.Shealsohasexperienceincommercialdocumentationandlitigationmattersforpharmaceuticalcompanies,mattersrelatingtotechnologyandmedialaws,andpublicprocurement.

ArtificialIntelligenceinHealthcare—NavigatingRegulatoryFrontiersinIndia

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EshikaPhadke

eshika.phadke@

EshikaisaLeaderinthePharmaceutical,Healthcare,MedicalDeviceandDigitalHealthTeam

atNishithDesaiAssociates.Shehasextensiveexperienceadvisingmultinationalcompaniesonregulatoryissues,compliances,marketingandpromotionalactivities,productlabellingandclaims,anti-trustrisks,publicprocurement,interactionswithgovernment,andcommercialdocumentation.Inherpreviousrole,Eshikaworkedcloselywithearly-stagestartupstoenablethemtobringtheirproducttomarket,asaresultofwhichshehaspracticalexperiencedealingwiththechallengesthatindustryplayersatvaryingstagesfaceacrosstheproductlifecycle.Shealsohasexperienceworkingwithhospitalsanddoctorstodefendmedicalnegligencesuits.

Dr.MilindAntani

milind.antani@

Dr.MilindAntani,arenownedsurgeonturnedlawyer,headsthePharmaceutical,Healthcare,MedicalDeviceandDigitalHealthpracticeaswellastheFood&Beveragespracticeatmulti-skilled,research-basedinternationallawfirm,NishithDesaiAssociateswhereherepresentshighnet-worthclientsinmattersalliedtoRegulatoryadvice,JVs,M&As,VCandPrivateEquityinvestments,Collaborations,LicensingandCommercialization.HealsoleadsSocialSectorPracticeandrepresentsvariousglobalandnationalfoundationsinIndia.

Dr.Antanicontinuesasanactiveparticipantinhelpingframenationalpoliciesonkeyimpactareas,withinthemedicalfield.

ArtificialIntelligenceinHealthcare—NavigatingRegulatoryFrontiersinIndia

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Contents

GlossaryofTerms3

5

Introduction

6

ApplicationsofAIinHealthcareandLifeSciences

A.Diagnostics6

B.AutomationofLaboratoryTesting6

C.ClinicalImaging7

D.ClinicalDecisionSupport7

E.PrecisionMedicine7

F.PredictiveModelling7

G.RoboticSurgery8

H.VirtualHealthAssistants8

I.ElectronicHealthRecords8

J.RemoteMonitoring8

K.MentalHealthcare9

L.Research&Development9

M.DrugDiscovery9

N.ClinicalTrialRecruitment10

O.GenomeEditing10

P.Bioinformatics10

ArtificialIntelligenceinHealthcare—NavigatingRegulatoryFrontiersinIndia

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ApproachtoRegulatingAIinHealthcare:GlobalPerspective11

A.UnitedStatesofAmerica11

B.UnitedKingdom12

C.EuropeanUnion13

14

RegulationofAIforHealthcareinIndia

A.RegulatoryBodies14

B.ApproachestoRegulationofAI15

C.OtherApplicableLaws17

23

ChallengestoRegulationofAIinIndia

I.LicensingRequirements23

II.ClinicalInvestigations23

III.Post-ApprovalChanges24

IV.Labelling24

V.Pricing24

VI.AdvertisingandClaims24

VII.PromotiontoHealthcarePractitioners25

26

RisksandEthicalChallenges

I.BiasandDiscrimination26

II.QualityofData26

III.Doctor-PatientRelationship26

IV.PrivacyandConfidentiality26

V.PhysicianPreparedness27

VI.Cybersecurity27

VII.EnvironmentalImpact27

ArtificialIntelligenceinHealthcare—NavigatingRegulatoryFrontiersinIndia

©NishithDesaiAssociates2025Provideduponrequestonly

Conclusion28

29

BeyondAI

A.VirtualRealityandAugmentedRealityinMedicalTrainingandEducation29

B.RoboticsinHealthcare30

C.NanotechnologyinDiagnosticImagingandDrugDelivery31

D.3DPrintedOrgans32

E.PredictiveAnalyticsinHealthcare33

F.PersonalizedMedicine34

ArtificialIntelligenceinHealthcare—NavigatingRegulatoryFrontiersinIndia

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ArtificialIntelligenceinHealthcare—NavigatingRegulatoryFrontiersinIndia

GlossaryofTerms

AbbreviationFullForm

AAEC

AppreciableAdverseEffectonCompetition

AI

ArtificialIntelligence

AR

Augmentedreality

CCI

CompetitionCommissionofIndia

CCPA

CentralConsumerProtectionAuthority

CDSCO

CentralDrugsStandardControlOrganization

CERT-In

IndianComputerEmergencyResponseTeam

ContractAct

IndianContractAct,1872

CPA

ConsumerProtectionAct,2019

DataProtectionRules

InformationTechnologyAct,2000,theInformationTechnology(ReasonableSecurityPracticesandProceduresandSensitivePersonalDataorinformation)Rules,2011

DCA

DrugsandCosmeticsAct,1940

DigitalCompetitionLaw

DigitalCompetitionBill,2024

DMRA

DrugsandMagicRemedies(ObjectionableAdvertisement)Act,1954

DPCO

Drugs(PriceControl)Order,2013

DPDPA

DigitalPersonalDataProtectionAct,2023

EHRs

ElectronicHealthRecords

EU

EuropeanUnion

GED

GenomeEditing

ICMR

IndianCouncilofMedicalResearch

IP

IntellectualProperty

LMPCR

LegalMetrology(PackagedCommodities)Rules,2011

MDR

MedicalDeviceRules,2017

MeitY

MinistryofElectronicsandInformationTechnology

MHRA

MedicinesandHealthcareProductsRegulatoryAgency

ML

MachineLearning

MoHFW

MinistryofHealthandFamilyWelfare

NHA

NationalHealthAuthority

NMC

NationalMedicalCommission

RMP

RegisteredMedicalPractitioner

SaMD

Software-as-a-Medical-Device

SPDI

SensitivePersonalDataorInformation

TelemedicineGuidelines

TelemedicinePracticeGuidelines,2020

TradeSecretsBill

ProtectionofTradeSecretsBill,2024

©NishithDesaiAssociates2025Provideduponrequestonly

5

ArtificialIntelligenceinHealthcare—NavigatingRegulatoryFrontiersinIndia

6©NishithDesaiAssociates2025Provideduponrequestonly

GlossaryofTerms

UCMPMDUniformCodeforMarketingPracticesinMedicalDevices

USAUnitedStatesofAmerica

USFDAUSFoodandDrugAdministration

VRVirtualreality

ArtificialIntelligenceinHealthcare—NavigatingRegulatoryFrontiersinIndia

Introduction

ArtificialIntelligence(“AI”)istransforminghealthcareglobally,andIndiaisemergingasoneofthemostdynamicregionsadoptingthiscutting-edgetechnology.TheadvancementsinAIhavethepotentialtooptimizepatientcare,streamlineadministrativeprocessesandimprovediseaseidentificationandmitigation.

Withitsvastanddiversepopulation,Indiafacesuniquechallengesinhealthcaredelivery,includingaccesstoqualitycare,ashortageofskilledhealthcareproviders,andtherisingburdenofchronicdiseases.AIhasthepotentialtoaddressthesechallengesbyimprovingtheaccuracyofdiagnoses,enhancingtreatmentplans,streamliningadministrativetasks,andmakinghealthcareservicesmoreaccessibletoremoteandunderservedpopulations.

Thechallengesposedbyanageingpopulation,theincreasingprevalenceofchronicdiseases,andtheescalatingcostsofhealthcarearepromptinggovernments,healthcareprovidersandconsumerstoseekinnovativesolutionsandtransformhealthcaredeliverymodels.TheCovid-19pandemichasforcedthehealthcareindustrytoimplementlarge-scaletransformationsby

integratingdata-driveninsightsintopatientcare.Thepandemichasalsounderscoredtheexistingshortagesinthehealthcareworkforceanddisparitiesinaccesstocare.Thegrowingavailabilityofdiversedatatypes,suchasgenomics,economic,demographic,clinical,andphenotypicdata,combinedwithadvancementsinmobiletechnology,computingcapabilities,anddatasecurityhasthepotentialtofundamentallyreshapehealthcaredeliverymodelsthroughAI-enhancedsystems.1

InIndia,AIhasstartedtorevolutionizevariousaspectsofhealthcare,rangingfromdiagnosticstodrugdiscoveryandpatientcare.ThecountryiswitnessingasurgeinAI-basedstartups,research,andcollaborationsbetweenhealthcareproviders,technologycompanies,andgovern-mentinstitutions,pavingthewayforAI-driveninnovation.Hegovernment’spushforNationalHealthStack,AyushmanBharat,andPradhanMantriJanArogyaYojanaarehelpingcreatethenecessaryecosystemforAI-poweredhealthcareinnovations.

Inthisresearchpaper,wehaveexploredthekeyareasofAIapplicationinhealthcareinthecountry,themannerofregulationofAItoolsandmodelsinthehealthcaresectorinotherjurisdictionsfollowedbytheassessmentofregulatoryframeworksurroundingAIinIndiaatpresent.WehavealsodiscussedthelegalchallengesfacedbythehealthcareindustryinadoptingandapplyingAI.

1Accessibleat:

/34286183/

.

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ArtificialIntelligenceinHealthcare—NavigatingRegulatoryFrontiersinIndia

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ApplicationsofAIinHealthcareandLifeSciences

AIisrapidlyreshapingthelandscapeofhealthcareandlifesciencesindustryinIndia,offeringtransformativesolutionstoaddresssomeofthecountry’smostpressinghealthcarechallengesandisunlockingnewfrontiersinresearch,innovation,andhealthcaredelivery.ByleveragingAI’scapabilities,Indiacanmoveclosertoachievinguniversalhealthcoverage,improvingpatientoutcomes,andcreatingamoreefficient,cost-effectivehealthcaresystem.

InthischapterweexplorethediverseapplicationsofAIacrossvarioussectorsofhealthcareandlifesciencesinIndia,includingdiagnostics,telemedicine,personalizedmedicine,acceleratingdrugdevelopment,improvingdiagnostictools,administrativeefficiency,anddrugdiscovery.

A.Diagnostics

TheevolutionofAIhaslongbeenlinkedtothediagnosisandtreatmentofdiseases,withsignifi-cantmilestonesdatingbacktothe1970s.Earlyrule-basedAIsystemsweredesignedtodiagnoseblood-bornebacterialinfectionsanddemonstratedpotentialforaccuratediseasediagnosisandtreatment,theystruggledtogainwidespreadadoptioninclinicalsettingsduetotheirinabilitytomatchtheaccuracyandclinicaljudgmentofhumanhealthcareproviders.1

Intherealmofdiseasediagnosis,amajorareaofAIresearchfocusesonanalysingdiversedatasources,includingdiagnosticimaging,genetictesting,electro-diagnosticprocedures,clinicallaboratoryresults,andphysicalexaminationnotes.

B.AutomationofLaboratoryTesting

AI’simpactonclinicallaboratoriesisalsonotable,especiallyinenhancingefficiencyandprecision.Automatedmethods,suchasthoseusedinbloodcultures,susceptibilitytesting,andmolecularplatforms,havealreadybecomestandardpracticeinmanylaboratories,significantlyimprovingefficiency.TheintegrationofAIintoclinicalmicrobiologylabscouldfurtheroptimizeprocesses,suchasselectingthemostappropriateantibiotictreatments,whichcouldimprovecureratesforinfectiousdiseases.Moreover,AIhasthepotentialtoshortenclinicaltrialdurations,increaseproductivity,andimproveclinicaldevelopmentoutcomes.Onemajorchallengeindrugdevelop-mentisnon-clinicaltoxicity,whichcontributestohighratesofdrugfailuresinclinicaltrials.Advancesincomputationalmodelling,however,areimprovingthepredictionofdrugtoxicity,refiningthedrugdevelopmentprocess.2

1Accessibleat:

/articles/PMC2464549/

.

2Accessibleat:

/publication/355069925_Applications_of_Artificial_Intelligence_AI_in_healthcare

_A_review.

ArtificialIntelligenceinHealthcare—NavigatingRegulatoryFrontiersinIndia

ApplicationsofAIinHealthcareandLifeSciences

C.ClinicalImaging

AnotherpromisingapplicationofAIistheautomatedclassificationofclinicalimaging,particu-larlyinradiology.ArecentanalysisofAI-basedmedicaldevicesapprovedintheU.S.andEuropebetween2015and2020revealedthatmorethanhalfwereapprovedforradiologicalapplications.Thistrendisdrivenbythelimitationsofhumanvisioninclinicalimaging.Thedevelopmentofdeeplearningalgorithmstodetecttumoursinmammogramsatearlierstages,leadingtoimproveddiagnosticaccuracyandbettertreatmentoutcomesforbreastcancerpatientsareasolutiontosuchhumanlimitations.Similarly,AIhasshownpromiseindetectinganeurysmslinkedtodiabeticretinopathy,usingdeeplearning-basedunsupervisedlearningtechniques.Researchhasdemon-stratedthatsuchAImodelscanachievestrongdiagnosticaccuracyandcost-effectiveness.

D.ClinicalDecisionSupport

AIassistshealthcareprovidersindiagnosingandtreatingpatientsbyanalyzingmedicalrecords,clinicalguidelines,andthelatestresearch.AI-powereddecisionsupportsystemscansuggestpersonalizedtreatmentplans,predictpatientoutcomes,andhighlightpotentialrisks,helpingtoreduceerrorsandimprovecare.

E.PrecisionMedicine

Precisionmedicineinvolvestailoringmedicaltreatmentsandinterventionstotheindividualcharacteristicsofeachpatient,suchastheirgeneticmakeup,lifestyle,andenvironment.TheintegrationofAIintoprecisionmedicineholdsthepromiseofimprovingdiagnosticaccuracy,treatmentefficacy,andpatientoutcomes.

AIplaysapivotalroleinthisfieldbyanalyzingvastamountsofdata,suchasgenomics,electronichealthrecords,andmedicalimaging,toidentifypatternsthatmaynotbeapparenttohumanclinicians.AI-poweredsystemsprovideclinicianswithevidence-basedrecommendationstailoredtotheindividualpatient’sneeds,helpingtooptimizetreatmentstrategies,reducemedicalerrors,andenhancepatientoutcomes.

F.PredictiveModelling

AImodelscanpredictdiseaserisk,progression,andtreatmentoutcomesbasedonpatient-specificdata.Bylearningfromhistoricalpatientdata,thesemodelsassistcliniciansinmakinginformeddecisionsaboutpreventionandtreatmentplans.

©NishithDesaiAssociates2025Provideduponrequestonly

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ArtificialIntelligenceinHealthcare—NavigatingRegulatoryFrontiersinIndia

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ApplicationsofAIinHealthcareandLifeSciences

G.RoboticSurgery

AIisusedinroboticsurgicalsystemstoassistsurgeonsinperformingpreciseandminimallyinvasiveprocedures.Robotscanenhancethesurgeon’sprecision,reducehumanerror,andshortenrecoverytimes.AIsystemscanalsoprovidereal-timefeedback,makingsurgerymoreefficientandsafer.

H.VirtualHealthAssistants

AI-drivenvirtualassistants,suchaschatbotsandvoice-basedsystems,providepatientswithmedicalinformation,answerquestions,andofferguidanceonsymptomsandmedications.Theseassistantscanalsoscheduleappointments,remindpatientsaboutmedications,andmonitorchronicconditionsremotely,improvingpatientengagementandcompliance.

I.ElectronicHealthRecords

Inparallel,healthcareorganizationsareincreasinglyadoptingAItoautomatelabour-intensive,high-volumerepetitivetasks.AIstartupsandcompaniesareaddressingtheneedfortoolsthatcanhandlethesedemandingactivities.OnesuchadaptationistheanalysisoflargedatasetsfromElectronicHealthRecords(“EHRs”),whichcontainbothstructureddata(i.e.laboratorytestsandprocedures)andunstructureddata(i.e.radiologyreportsanddischargesummaries).ThecomplexityandvarietyofdatawithinEHRsmakethemdifficulttoanalysemanually,butAItechniquesenabletheprocessingofthisinformationtoenhanceunderstandingofthemedicalhistory,geneticmarkers,andfamilyhealthrisksofthepatient.3

J.RemoteMonitoring

AIenablesremotemonitoringofpatientsthroughwearabledevicesandsensorsthattrackvitalsigns,physicalactivity,andotherhealthmetricsinreal-time.AIalgorithmsanalyzethisdatatodetectearlysignsofdeteriorationordiseaseprogression,allowingforearlyinterventionandreducinghospitalreadmissions.

3Accessibleat:

/articles/PMC11141850/

.

ArtificialIntelligenceinHealthcare—NavigatingRegulatoryFrontiersinIndia

ApplicationsofAIinHealthcareandLifeSciences

K.MentalHealthcare

Traditionally,mentalhealthcarepractitionersrelyondirectinteractionsandbehavioural

observationstodiagnoseandtreatmentalhealthconditions.However,AI-poweredtoolscanenhancethesecapabilitiesbyassistinginearlydetectionanddiagnosis.Thesetoolscangeneratecustomizedtreatmentplansandprovidecontinuoussupport,bridgingresourcegaps,promotingastigma-freeenvironment,andcomplementingprofessionalexpertise.Inthisway,AIholdspromiseinaddressingtheevolvingchallengesofmentalhealthcare.4

RecentadvancementshavealsoenabledAItodeveloppersonalizedtreatmentplansusingintel-ligentalgorithms.Thesealgorithmsanalysepatientdata,incorporatinggenetic,lifestyle,andenvironmentalfactorstorecommendthemosteffectiveandcost-efficienttreatmentstailoredtoindividuals.Furthermore,AI-powereddigitaltools,suchasvirtualtherapistsandchatbots,havesignificantlyincreasedthescalabilityandaccessibilityoftherapeuticinterventions.5

L.Research&Development

Thebiotechnologysectorgeneratesvastdatasetsthatrequiresophisticatedmethodsforstorage,filtering,andanalysis.TheintegrationofAI-driventechnologies,particularMachineLearning(“ML”)andDeepLearning,istransformingtheefficiency,accuracy,andspeedofresearchanddevelopmentinmedicalbiotechnology.AIcananalysedatafromdiversesources,uncoveringinsightsthatwouldbedifficultforhumanresearcherstoidentify.6ByharnessingthepowerofAI,thebiotechnologyindustryispoisedtomakesignificantstridesinimprovingpatientcare,optimizingtreatmentoutcomes,andboostingtheoverallefficiencyofhealthcaresystems.

M.DrugDiscovery

AIacceleratesthedrugdiscoveryprocessbypredictingtheinteractionsbetweenmoleculesandbiologicaltargets,identifyingnewdrugcandidates,andoptimizingclinicaltrialdesigns.Itcanalsoassistinrepurposingexistingdrugsfornewdiseases,speedingupthedevelopmentoftreat-mentsandreducingcosts.

4Accessibleat:

/doi/epdf/10.2147/RMHP.S461562?needAccess=true

.

5Accessibleat:

/science/article/pii/S2949916X24000525

.

6Accessibleat:

/articles/ai-and-machine-learning-in-biotechnology-a-paradigm.pdf

.

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ApplicationsofAIinHealthcareandLifeSciences

N.ClinicalTrialRecruitment

AIcanstreamlinetheclinicaltrialprocessbyidentifyingsuitablecandidatesfortrialsbasedonpatientdata,improvingtherecruitmentprocess.Itcanalsomonitortrialdatainreal-time,makingiteasiertodetectproblemsoradjustprotocolsquickly.

O.GenomeEditing

GenomeEditing(“GED”)allowsforgeneticengineeringbyinserting,deleting,modifying,orreplacingthe