Intelligent Implants and Drug Delivery Systems

14 Pages·2017·10.07 MB·English

Journal of
Functional
Biomaterials
Article
Implementation of Industrial Additive
Manufacturing: Intelligent Implants and Drug
Delivery Systems
JanSherAkmal1,* ID,MikaSalmi1 ID,AnttiMäkitie2 ID,RoyBjörkstrand1andJouniPartanen1
1 DepartmentofMechanicalEngineering,AaltoUniversity,02150Espoo,Finland;mika.salmi@aalto.fi(M.S.);
roy.bjorkstrand@aalto.fi(R.B.);jouni.partanen@aalto.fi(J.P.)
2 DepartmentofOtorhinolaryngology–HeadandNeckSurgery,UniversityofHelsinkiandHelsinki
UniversityHospital,00029Helsinki,Finland;antti.makitie@helsinki.fi
* Correspondence:jan.akmal@aalto.fi;Tel.:[phone]
(cid:1)(cid:2)(cid:3)(cid:1)(cid:4)(cid:5)(cid:6)(cid:7)(cid:8)(cid:1)
(cid:1)(cid:2)(cid:3)(cid:4)(cid:5)(cid:6)(cid:7)
Received:31May2018;Accepted:27June2018;Published:29June2018
Abstract: Thepurposeofthisstudyistodemonstratetheabilityofadditivemanufacturing, also
known as 3D printing, to produce effective drug delivery devices and implants that are both
identifiable,aswellastraceable. Drugdeliverydevicescanpotentiallybeusedfordrugreleasein
thedirectvicinityoftargettissuesortheselectedmedicationrouteinapatient-specificmanneras
required.Theidentificationandtraceabilityofadditivelymanufacturedimplantscanbeadministered
throughradiofrequencyidentificationsystems. Thefocusofthisstudyistoexplorehowembedded
medicationandsensorscanbeaddedindifferentadditivemanufacturingprocesses. Theconceptis
extendedtobiomaterialswiththehelpoftheliterature.Asaresultofthisstudy,apatient-specificdrug
deliverydevicecanbecustom-designedandadditivelymanufacturedintheformofanimplantthat
canidentify,trace,anddispenseadrugtothevicinityofaselectedtargettissueasapatient-specific
functionoftimeforbodilytreatmentandrestoration.
Keywords: additivemanufacturing;3Dprinting;biomaterials;parametricmodeling;drugdelivery
systems;embedding;medicine;radiofrequencyidentification;objectmemory;internetofthings
1. Introduction
Additivemanufacturing(AM),non-technicallyknownas3Dprinting,isaprocessinwhichmaterial
isaddedandjoinedtypicallyonalayer-by-layerbasistomakeproductsusingdigitaldataofa3Dmodel,
contrarytosubtractivemanufacturingandformativemanufacturingmethodologies[1].Eversincethe
instigationoftheconceptintheearly1980s[2],ithasbeenwidelyusedinabroadrangeofindustries,
including military, aerospace, automotive, energy, and biomedical fields [3,4]. Tuomi et al. [5] have
presentedaclassificationformedicalapplicationsofAMthatincludesmedicalmodelsforplanning,
medicalaids,toolsformedicaldevices,inertimplants,andbio-manufacturing.Thefocusofthisstudy
istoextendthecapabilityofAMinbiomedicalfieldviaadditively-manufacturingimplantscontaining
custom-designeddrugdeliverysystemsequippedwithradiofrequencyidentificationtechnologiesfor
restoration of bodily harm. To this end, the composition of such a delivery system must be inert
and compatible with the human body, which inevitably limits the use to biomaterials. Tappa and
JammalamadakahaveclassifiedbiomaterialsusedinAMintofourcategoriesthatincludemetalandits
alloys,ceramicsandcarboncompounds,polymers,andcomposites[6]. AccordingtotheISO/ASTM
52900:2015(en) standard, AM contains seven process categories that mainly differentiate each other
through the techniques that they use for the layer-by-layer fabrication of their compatible materials.
Hence,theselectionofasuitablebiomaterialdependsontheapplicationthatspecifiesitsphysicaland
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mechanicalpropertiesfollowedbyitscompatibilityofbeingadditivelymanufacturedthroughoneof
theISO/ASTMadditivemanufacturingprocesses.Table1presentsthebiomaterialsthatarecompatible
witheachoftheAMmethodsthatareutilizedinthisstudytoprovideproofofconcept. Theuseof
additively-manufacturedbiomaterialsmustalwaysbeprecededwithmedicalconsiderations.
Table1.BiomaterialswithrespecttotheISO/ASTMAMmethods.
ISO/ASTMAdditive
CompatibleBiomaterials Source
ManufacturingMethod
Polycaprolactone(PCL)
Polylactide(PLA)
MaterialExtrusion(ME) Polycarbonate(PC) [6–9]
Polyvinylalcohol(PVA)
Polylactic-co-glycolicacid(PLGA)
Poly-ε-caprolactone
Polylactide-coglycolide
Poly-L-lacticacid

Starch

Dextran +water
BinderJetting(BJ) Gelatin  [10–15]
Peptides
Proteins(e.g.,fibrinogen,collagen)
Polysaccharides(e.g.,hyaluronan,alginate)
DNAplasmids
Livingcells
Polypropylenefumarate(PPF)
VatPhotopolymerization(VP) Polycaprolactone(PCL) [9,16,17]
DentalSGResin
PCL
Polyetheretherketone(PEEK)
PVA+Hydroxyapatite(HA)
PowderBedFusion(PBF) PEEK+HA [18–25]
Calciumphosphate
Titanium
TiAL6V4ELI
One of the key factors that influence various treatment approaches of human health is drug
deliverytothetargettissues.Drugdeliverytypicallyinvolvesvariousapproaches,systems,technologies,
andformulationsforthereleaseofanactivepharmaceuticalingredienttothepatientthroughdifferent
methods and shapes, as required [26,27]. These include, for example, intravenous, intra-articular,
intramuscular, cutaneous, subcutaneous, mucosal(intraoral, intranasal, rectal), andpulmonarydrug
administration. The effectiveness of different drug delivery systems is measured over the course of
timethroughinvitroand/orinvivotestingthatmaybeassociatedwithimmediateorlong-termside
effects.Deliveringthedruglocallynearthedamagedtissuehasshowngoodresultsinseveralsubjectsof
treatment[28].Thisisrelevanttoenhancetheaccuracyofaselectivetreatmentandalsotoshortenthe
timebeforetheonsetofdrugeffect.Furthermore,sideeffects,andevencomplicationsinhealthytissues,
maybeavoidedwhendrugreleaseislocatedclosetothetargettissueororgan.
Various conditions of the temporomandibular joint (TMJ) affect roughly one quarter of the
population,andpossiblecausesincludeinjury,arthritis,andgenetics,i.e.,certainconnectivetissue
disorders[29]. Thetherapeuticoptionsareusuallynon-surgicalandmanagedinprimaryhealthcare,
whereascomplicatedcasesrequirecarebyaspecialistandsurgeryispreservedasthelastalternative.
Recently,tissueengineeringhasbeeninvestigatedasanemergingalternativeforreplacingdiseased,
displaced,ordegeneratedtissuesintheTMJ[29].
Duetothenatureofpatient-specificanatomicalgeometry,thereisnoone-size-fits-allapproach
to replace a defective part of the body. Therefore, patient-specific planning is needed. There are
differentmethodstoacquirepatientanatomyintocomputeraideddesign(CAD)thatisneededfor
novelmedicalplanningwork. 3Dscanningmethods,suchasmagneticresonanceimaging(MRI)and
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computedtomography(CT),complementsuchaphenomenonbycapturingdatafromtheinterior,
aswellastheexterior,ofthepatient-specificanatomicalgeometry[30]. Themedicalimagingdata
acquiredfromthesemethodsarestoredaccordingtotheinternationalstandardofdigitalimaging
and communications in medicine (DICOM) format, which resembles a block of raw data that is
generallyinspectedina2Dmannerbypractitionersinthefield. Hence,3Dthresholdingtechniques
viz. volume-basedmethods,contour-basedmethods,and/orpoint-cloud-basedmethodsareusedto
acquirethenecessary3Ddataoftheanatomicalmodels[31]. Salmi[32]haseffectivelyevaluatedfive
differentanatomicalmodels,includingpelvis,knee,backbone,ankle,andheart,throughCTscanning
followedbyvolume-basedthresholding,3Dmodelingand,eventually,AM.
Radiofrequency identification (RFID) involves detecting and recognizing physical object(s)
wirelesslythroughradioorelectromagneticcommunications[33,34]. RFIDtechnologieshavebeen
usedinavastrangeofindustriessuchasmanufacturing,supply-chainmanagement,andlogistics[35].
Itsapplicationsalsoextendtoanimaltracking[36–38],food[39],andhealth[40].RFIDsystemsinclude
atransceiver/reader,atransponder/tag,andtwoantennasforcommunication[41]. Thereaderemits
radiowavesintherangeofelectromagneticspectrumtocommunicatewiththetagthatcarriesaunique
identifier.Thetagcanbeeitheractive—equippedwithapowersource—orpassive—notequippedwith
apowersource. Passivetagshavebeenwidelyimplantedintoanimalsthroughhollowneedleinjection
undertheskinoftheanimal[38].Therangeofcommunicationbetweenthereaderandthetagdepends
onthepoweroutputandtheradiofrequencythatisused[33]. Theradiofrequencyrangeisdefined
by the ISO standards as low frequency (LF); <135 kHz, high frequency (HF); 13.553–13.567 MHz,
andultra-highfrequency(UHF);433MHzto2.45GHz[41]. Thesignificantprogressinlow-power
semiconductorandmicroelectronicstechnologiesequippedwiththere-usabilityoftheRFIDsystems
andproductivitygainshavepromotedtheuseofRFIDsystemstobecomemoreaffordable[42].
The aim of this study is to demonstrate the ability of embedding conceptual medication and
RFIDtranspondersintoanadditively-manufacturedimplantusingdifferentAMtechniques. Tothis
end,aconceptualcasescenario,includingadrugdeliverysystemandanRFIDsystem,wasdesigned
tobefabricatedviaanadditively-manufacturedimplantinordertoidentifyanddeliveraspecific
drugforthetherapeutictreatmentofvariousconditionsoftheTMJ.Theconceptispresentedthrough
conventionalmaterialsusedforAM,however,itcanbeimplementedusingbiomaterialsthathave
beenstudiedthroughouttheliteraturepresentedinTable1.
2. Results
The results of the additively-manufactured implant fused to its corresponding mandible can
beseeninFigure1usingtheISO/ASTMAMmethodsshowninTable1. Theresultsofoperational
communicationbetweenthetransponderandtransceivercanbeseeninTable2. Accordingtothese
results,allthetestedAMmethodswereabletosuccessfullymanufacturethemandibleanditsimplant
toafinedetail, includingtheembeddeddrugdeliveryandRFIDsystems. Thelevelofdetailwas
inverselyproportionaltothelayerthicknessofdifferentmethods. Upontesting,theintelligentimplant
wasabletoidentifyitselfandcommunicatethenecessarypatient-specificinformationinallcases.
Table2.ResultsofembeddedRFIDsystems.
EmbeddedISOHFRFIDData EmbeddedISOUHFRFIDData
ISO/ASTMAMMethod
Communicated[Yes/No] Communicated[Yes/No]
ME Yes Yes
VP Yes Yes
BJ Yes Yes
PBF Yes Yes
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(a) (b)

(c) (d)

(e)
Figure 1. Additively manufactured mandible with embedded conceptual drug and RFID
Figure1.AdditivelymanufacturedmandiblewithembeddedconceptualdrugandRFIDtransponders
transponders using: (a) the material extrusion method; (b) RFID transmission with the material
using:(a)thematerialextrusionmethod;(b)RFIDtransmissionwiththematerialextrusionmethod;
e(cx)trtuhseiovna tmpehthootodp; (ocl)y tmhee rvizata tpiohnotompeotlhyomde;r(idza)titohne mbientdheord;j e(tdt)in tghem beinthdoedr ;jeattnindg( me)etthheodp; oawndd e(er)b tehde
pfuoswiodnemr beethdo fdu.sion method.
J.Funct.Biomater.2018,9,41 5of14
3. Discussion
Thecapabilitiesofadditivemanufacturing,or3Dprinting,havebroadenedthedesignfreedom
andapproachofmanufacturingthroughouttheindustries. Theseuniquecharacteristicsallowforthe
implementationofnovel,patient-specificapplicationsinthefieldofmedicine. Thisstudyallowsfor
custom-designed,additivelymanufactureddrugdeliverysystemsforcontrolleddrugdispensingin
directvicinityofneed,whichcanenhancebodilyrestorationandlowertherisksofunintendedside
effectsofotherbodilyfunctions. Thisisachieved,forexample,throughembeddingtheconceptual
medication in an implant. In the present case, the right part of a mandible was used as a model,
and eight controlled channels were created for dispensing. The drug release or activation will
typicallyinvolveavarietyofmechanisms,i.e.,diffusion,degradation,swelling,andaffinity-,route-,
ordosage-basedmechanisms, andneedstobedesignedseparatelyineachindividualapplication.
The dispensing channels can also be manufactured through such biomaterials that dissolve over
time and release the drug to the target tissue as required. This study also allows for storage of
patient-specific information including the identification of the drug and/or the implant through
passiveradiofrequencyidentificationtransponders,whicharealsoembeddedintotheimplantatthe
sametimeasthemedication. Whentheimplanthasbeenmanufacturedwiththeaforementioned
embeddedelements,itcanbesurgicallyinsertedintotherequiredarea. Subsequently,theprovided
conceptallowsforidentifyingandreadingpatient-specificinformationfromoutsidethebodyusing
anRFIDtransceiverwithoutanyinvasiveprocedures. Thepatient-specificinformationcanrepresent
thedigitalversionofthedocumentationthatpatientsnormallyreceivepostoperatively. Thismay
include information on the patient, implant, and treatment, such as the name of the patient and
theembeddedmedicine,dateofbirth,dateofmanufactureoftheimplant,materialoftheimplant,
and/orpossibleexpirationoftheimplant. Thiscanensureaccesstothepatient-specificinformation
throughtheInternetofThings(IoT)evenwhensuchphysicaldocumentationislost. Theconceptalso
allowsforobtainingadigitaltwinoftheimplant,forinstance,throughanidentifier,whichwillenable
reproductionoftheimplant. Contrarytothecurrentindustrialpracticeofadigitaltwin,thiswould
requireawiderrangeofregulationstobeimplementedinthefieldofmedicine.
TheparametricnatureofdrugdeliveryandRFIDcavitysystems,developedinthisstudy,allow
designautomationwithauserinterfacethatcanaidin3Dmodelingevenbysomeoneunfamiliarto
theart. Thisensuresahighdegreeofeaseofuseforpractitionersinthefieldofmedicinewhoare
typicallyunfamiliarwithsuchdesignmethods. Themodelsallowforcontrolleddrugdeliveryviathe
size,length,andnumberofdispensingchannels. Toensurethatnomaterialisjoinedtogetherinthe
cavityintendedforbothdrugandRFID,asupportfeatureisaddedtothemodelsthatterminatessuch
fusionofmaterial. SincedifferentAMtechnologieshavedifferentparameters,suchasminimumlayer
thicknessorresolution,aprintclearancefeatureisalsoautomatedinthemodels. Thisensuresthat
thereisenoughroominthecavityforembeddingtheintendedsystem.
Inthisstudy,theimplant,therightpartofamandible,isadditivelymanufacturedinconnection
withitsintendedanatomicalmodel,themandible,fordemonstrationpurposes. Thiscanprovidea
visualaidtothesurgeonsasapre-operativeplanningtoolthatcanserveasaguideforpinpointing
theintendedincisionsanddrillingforimplantation. Subsequently,theimplantwiththeembedded
infrastructurecanbeprintedbyitselfandimplantedthroughsurgery. Inthiscase,theprintingtimes
recorded in Table 2 can be up to 80% lower. All the AM methods that were used for this study
provided an efficient way of embedding custom drug delivery and RFID systems in implants for
controlleddeliveryandelectronicstorageofpatient-specificinformation. Afewdelaminationissues
wereencounteredforpowder-basedAMmethodswhenthemachinewaspausedfortoolongwith
anopenbuildchamber. InthecaseoftheBJmethod,thisiscausedduetotheusageofacommercial
machinethatdoesnotallowforvariationinbinderdispersion. SimilarlyforthePBFmethod,this
occursbecauseoftheformationoflargethermalgradients.
For future developments, the practice of embedding can be easily made free of human error,
delaminationproblems,andissuesrelatedtohygienethroughaglovesystemoranautomatedrobotic
J.Funct.Biomater.2018,9,41 6of14
system where build chambers stay intact. The presented concept can also be extended to other
applications that can benefit from embedding drug delivery and/or RFID systems in the medical
field. For instance, it is a common practice for those who suffer from severe arthritis in knees to
havethemreplacedbytitaniumimplants. Inthiscase,thisconceptcanaidinprovidingamedicinal
lubricant,i.e.,synovialfluid,tothedesiredcontactsforreducingfrictionandstressshielding. Since
kneeimplantstypicallyhavealifecycleof10–15years,dependingonthecase,anRFIDtransponder
canstoresuchpatient-specificinformationforfuturefollow-upsandeventualreplacement. Expanding
itsscopefurther,theconceptcanalsobeusedforlubricatingmovingcomponentsinotherindustries
forreductionoffrettingandgallingwearfoundinbearings,forinstance. RFIDsystemscanaidin
identifying parJ.t Fsuntcth. Baiotmaaterr. e201n8, o9, tx FeOaRs PiElEyR RaEVcIcEeWs sible and/or are subject to wear and6t eofa 1r4 where the use
of other identifiFocra intsitoanncem, ite ist ha coodmsm,osnu pcrahcticaes foor pthtoisce awlhroe sucfofegr nfriotmio snev,eries ardthirfifitisc iun lktn.eeTs tho ihsavcea thnema lso provide an
infringement-prreoploacfeds obylu tittaioninums iimnpcleantths. eInp thaisr tcawse,o thuisl dconhcaepvt ecatno aibd ein dpreosvtirdoinyg ea dmeidnicoinradl leubrritcoanat, ccesstheRFID.
i.e., synovial fluid, to the desired contacts for reducing friction and stress shielding. Since knee
Moreimportantly, thisstudyhasinvestigatedfourISO/ASTM-definedAMmethodstoprovidea
implants typically have a life cycle of 10–15 years, depending on the case, an RFID transponder can
proofofconcepstto.reT shuceh rpeatsietnot-fsptehciefict ihnfroermeamtioent fhoro fdutsu,red fiorlleocwt-eudps eannde ervgeyntudale rpepolascietmioennt. (EDxpEanDd)in,gm aterialjetting
its scope further, the concept can also be used for lubricating moving components in other industries
(MJ),andsheetlamination(SL),canalsobestudiedforfuturedevelopment.
for reduction of fretting and galling wear found in bearings, for instance. RFID systems can aid in
identifying parts that are not easily accessible and/or are subject to wear and tear where the use of
4. MaterialsanodthMer eidtehntoifdicastion methods, such as optical recognition, is difficult. This can also provide an
infringement-proof solution since the part would have to be destroyed in order to access the RFID.
ForthepuMrporoe siempoofrttahntilsy, stthuis dstyu,dfyo huasr iInSvOest/igAateSdT foMur- dISeOfi/AnSeTMd-AdefMinedm AeMth moedthsodws etor epruovsieded at odemonstrate
proof of concept. The rest of the three methods, directed energy deposition (DED), material jetting
theabilityofadditivelymanufacturingimplantsthatareequippedwithcustom-madedrugdelivery
(MJ), and sheet lamination (SL), can also be studied for future development.
systemsandRFIDs. Thesewerematerialextrusion(ME),vatphotopolymerization(VP),binderjetting
4. Materials and Methods
(BJ),andpowderbedfusion(PBF).TheprocessassociatedwiththesemethodsispresentedinFigure2.
For the purpose of this study, four ISO/ASTM-defined AM methods were used to demonstrate
Theprocessinitiatesfrom3DscanningoftheanatomicalmodelusingCTscanninginDICOMformat.
the ability of additively manufacturing implants that are equipped with custom-made drug delivery
After that, a vosylsutemmse -abnda sReFdIDs3. DThetshe rweesrhe omladteirniagl etxetrcuhsinoni q(MuEe), wvaat sphuotsoepdolytmoersizeagtiomn e(VnPt), tbhinedevr oxel data with
regardtograyscjeattlinega (BlgJ)o, arnidth pmowdoefr mbeda frucshioinn (gPBcFu). bThees ptroocoesbs taassionciathteed wpiatht itehenste- mspetehocdifis ics pgreesoemnteedt irny . Subsequently,
Figure 2. The process initiates from 3D scanning of the anatomical model using CT scanning in
theintendedimDpIClaOnMt fworamsat3. ADftemr tohadt,e al veodluwmei-tbhasreeds 3pDe thcrtetshootldhinego tebcthaniiqnueed wagse uosemd teot sreygmfoenllt othwe veodxebl y3Dmodeling
ofincorporatedddatra uwgithd reegliavrde rtoy garanydscaRleF aIlgDoristhymst oefm msar.ch3iDng mcuboeds etol ionbgtaion fthteh peatliaenttt-espretcwifico gesoymsetterym. sinvolvesAM
Subsequently, the intended implant was 3D modeled with respect to the obtained geometry followed
parametersthatarespecifictoeachmethod. Thefollowingsectionelaboratesonthisprocessaccording
by 3D modeling of incorporated drug delivery and RFID systems. 3D modeling of the latter two
tothemethodssuyssteemds iinnvothlviess AstMu pdayra.meters that are specific to each method. The following section elaborates
on this process according to the methods used in this study.

Figure 2. Process of additively manufacturing (3D printing) intelligent implants and drug delivery
Figure2.Processofadditivelymanufacturing(3Dprinting)intelligentimplantsanddrug
systems.
deliverysystems.
4.1. Mandible Implant
4.1. MandibleImplaTnhte specimen selected for this study was a mandible that depicts the lower jaw of the human
anatomy. The mandible is connected to the TMJ, which is one of the strongest joints in the human
body. The data were obtained from a 63-year old patient using GE Lightspeed (GE Healthcare,
Thespecimenselectedforthisstudywasamandiblethatdepictsthelowerjawofthehuman
Chicago, IL, USA) computed tomography with 120 kVp. The scanning was performed in helical mode
anatomy. Themwaitnhd laiybelre thiisckcnoesns nofe 1c.2t5e dmmto. Tthhe etoTtaMl nuJm,wbehr oicf lhayiesrso wnaes 2o0f3. tThhee psattrioennt ghaeds at djoisionritesntiantedth ehumanbody.
Thedatawereombatnadiibnlee wditfhr othme maain6 p3a-ryt eofa irts orilgdht psiadet ieenntirteluy sminissginGg. ELightspeed(GEHealthcare,Chicago,IL,

USA)computedtomographywith120kVp. Thescanningwasperformedinhelicalmodewithlayer
thicknessof1.25mm. Thetotalnumberoflayerswas203. Thepatienthadadisorientatedmandible
withthemainpartofitsrightsideentirelymissing.
J.Funct.Biomater.2018,9,41 7of14
The 3D model of the anatomy was segmented using Osirix (2.7.5, Pixmeo SARL, Geneva,
J. Funct. Biomater. 2018, 9, x FOR PEER REVIEW 7 of 14
Switzerland) with 500 HU density, 0.5 decimate, and 20 smoothing iterations. First, the mandible
wasmovedtoTthhee 3cDo rmreocdtello ocfa tthioe nasn.at3oDmym woads esleingmgeonftetdh eusiimngp Olasniritxw (2a.7s.5d, oPnixemueos inSAgR3LD, GateaneEvxa,p ert(11.0,
Switzerland) with 500 HU density, 0.5 decimate, and 20 smoothing iterations. First, the mandible was
DeskArtes,Helsinki,Finland)andVisCamRP(3.6,MarcamEngineering,Bremen,Germany)according
moved to the correct locations. 3D modeling of the implant was done using 3Data Expert (11.0,
tothespecificationsofthesurgeon. Thestartinggeometrywasmirroredfromtheleftside,whichwas
DeskArtes, Helsinki, Finland) and VisCam RP (3.6, Marcam Engineering, Bremen, Germany)
eventualJl.y Fuapncccoto. sBridiotmiinoagtne rt.eo 2d 0t1h8ae, n9s,p dxe FcfOiofRirc PmaEtEieoRdn RsE toVofI EtfihWte osunrgtehoen.r Tigheh sttasritdineg. gTehomeesturyp wpaosr mtinirgrorsetdru frcotmu rtehew 7le iofttf hs1i4ds ec,r ewholes
wasaddedwohvicehr wthase ejvaewntutoallkye peopsittihoneeidm apndla fnortminedi ttso fdite osnig thnea rtiegdhtp slidaec.e T.hTe hsuepfipnoratlinmg sotdruecltuorfe twhiethm andible
The 3D model of the anatomy was segmented using Osirix (2.7.5, Pixmeo SARL, Geneva,
screw holes was added over the jaw to keep the implant in its designated place. The final model of
connecteSdwtiotzeitrslanimd)p wliathn t50c0a HnUb deesneseitny, i0n.5 Fdeigciumraete3, .and 20 smoothing iterations. First, the mandible was
the mandible connected to its implant can be seen in Figure 3.
moved to the correct locations. 3D modeling of the implant was done using 3Data Expert (11.0,
DeskArtes, Helsinki, Finland) and VisCam RP (3.6, Marcam Engineering, Bremen, Germany)
according to the specifications of the surgeon. The starting geometry was mirrored from the left side,
which was eventually positioned and formed to fit on the right side. The supporting structure with
screw holes was added over the jaw to keep the implant in its designated place. The final model of
the mandible connected to its implant can be seen in Figure 3.

Figure 3. 3D scanned, rendered and modeled patient-specific mandible (maroon) connected to its
Figure3. 3Dscanned,renderedandmodeledpatient-specificmandible(maroon)connectedtoits
implant (white).
implant(white).
4.2. Parametric Drug Delivery System
4.2. ParametricAD drurugg Ddeelliivveerryy coSnycsetpetm was custom-designed using Creo Parame tric (3.0, PTC, Needham, MA,
USA) through a parametric model that allows for seven custom inputs with regard to the medicine
AdrugFdigeulirve e3.r y3Dc socnancneepd,t rwenadesrecdu asntdo mmo-ddeelesdi gpnateiednt-uspseicnifgic CmraenodibPlea (rmaamroeotnr) iccon(3ne.0ct,ePd TtoC it,s Needham,MA,
of need. It is based on a conceptual tablet drug, shown in Figure 4, that is, in fact, an HF RFID
implant (white).
USA)throutrganhspaopndaerra. mTheet rdiicmmenosidonesl tohf athtea lcloonwcesptfuoarl dseruvge nmactuchs twomell iwnipthu tthsew cointhvernetigoanradl rtaongteh eof medicine
of need.4.I2tt.a Pibsalerabtsma teshtreaitdc aDroerun tga kaDeencli ovoenrracyll eySp ywsttuhemean l nteaebdleedt. Adnru agct,ivsithyo dwiagnraimn oFfi tghuisr pear4a,mtehtraict miso,dienl offa tchte, darung HF RFID
cavity can be seen in Figure 5. The model also allows for a controlled rate of drug delivery or
transponder.AT dhreugd dimelievnersyi oconnscoepftt whaesc counstcoemp-tduesailgnderdu ugsimnga Ctcrheow Paerlalmweittrhic (t3h.0e, cPoTnCv, Neneetdiohnamal, MraAn,g eoftablets
dispensing with inputs of number, size, and length of channels that can be seen spiraling away in
thataretUaSkAe)n thorroaulglhy aw phareanmneteriecd meodd.elA thnata acltliovwist yfodr isaevgerna cmusotofmt hinipsuptsa wraitmh eretgraicrdm too tdhee lmoefdtichineed rugcavity
opposite directions from the drug cavity in Figure 6. Since ME and VP methods require support
of need. It is based on a conceptual tablet drug, shown in Figure 4, that is, in fact, an HF RFID
canbeseenstriunctFuirgesu drueri5n.g Tthhee mmanoudfaecltuarilnsgo parlolcoewss stof roersiast cgoranvtitryo floler dsurrfaatcee oovfedrhraunggs dofe alibvoevrey 45o°,r thdei spensing
transponder. The dimensions of the conceptual drug match well with the conventional range of
with inputmsoodfeln isu amlsob einrc,osripzoera,teadn wditlhe na gsuthppoorft cfehaatunren ethlast trhematovceas ntheb eaustoemenatisc psuirpaploirnt gstrauwctuaryesi onf opposite
tablets that are taken orally when needed. An activity diagram of this parametric model of the drug
the printer related software, when activated. This feature can be seen in Figure 6a when it is
directioncsavfirtoy mcant hbee dsereung inc aFvigiutyre i5n. TFhige umroed6el. aSlsion caelloMwsE foarn ad cVonPtromlleedth roatde sorf edqruugir deesliuveprpy oorrt structures
deactivated for powder-based methods of BJ and PBF, and in Figure 6b when it is activated for ME
duringthdeispmenasninugf wacitthu irnipnugtsp orfo ncuemssbetro, sriezes,i satndg rleanvgitthy offo crhasnunreflasc tehaot vcaenr hbae nsegesn ospfiarablionvge aw45ay◦ ,inth emodelis
and VP methods. Once the model was recreated in the computer aided design system according to
opposite directions from the drug cavity in Figure 6. Since ME and VP methods require support
alsoincorptohrea dteesdirewd iitnhpuat spuarpapmoetretrsf,e iat twuarse inthseartterde imntoo vthees dtihgietaal uimtoplmanat tfiocr sBuooplpeaonr stusbttrruaccttiuonr etos foofrmth eprinter
structures during the manufacturing process to resist gravity for surface overhangs of above 45°, the
related sofittws gaeroem,ewtrihcaeln caavcittyi vuasitnegd I.nsTpihrei s(2f0e1a7.t3u.2r,e SoclaidnThbienksinege,n Triony,F MigI,u UrSeA6).a when it is deactivated for
model is also incorporated with a support feature that removes the automatic support structures of
powder-bthaes epdrinmtere trheloadtesd osfofBtwJaarne,d wPhBenF ,aacntidvaitnedF. iTghuisr efe6atburwe hcaenn bite isseeanc tiinv aFtiegduref o6ra MwEheann idt iVs Pmethods.
Oncethedmeacotidveatlewd faosr preowcrdeeart-beadseidn mthetehocdosm ofp BuJ taenrda PiBdFe, dandde isni Fgingusrye s6tbe wmheanc cito isr dacintivgatteod tfhore MdEe siredinput
and VP methods. Once the model was recreated in the computer aided design system according to
parameters,itwasinsertedintothedigitalimplantforBooleansubtractiontoformitsgeometrical
the desired input parameters, it was inserted into the digital implant for Boolean subtraction to form
cavityusingInspire(2017.3.2,SolidThinking,Troy,MI,USA).
its geometrical cavity using Inspire (2017.3.2, SolidThinking, Troy, MI, USA).

Figure 4. Conceptual tablet drug: HF RFID transponder conferring to ISO18000-3.

Figure 4. Conceptual tablet drug: HF RFID transponder conferring to ISO18000-3.
Figure4.Conceptualtabletdrug:HFRFIDtransponderconferringtoISO18000-3.
J.J.F Fuunncctt.. BBiioommaatteerr.. 22001188,, 99,, x4 1FOR PEER REVIEW 0 8ofo f114 4

Figure 5. Activity diagram of a parametric drug delivery system consisting of seven design-based input parameters.
Figure5.Activitydiagramofaparametricdrugdeliverysystemconsistingofsevendesign-basedinputparameters.
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(a) (b)
(a) (b)
Figure 6. Drug delivery cavity consisting of eight dispensing channels and a support feature that is:
Figure 6. Drug delivery cavity consisting of eight dispensing channels and a support feature that is:
Figure6.Drugdeliverycavityconsistingofeightdispensingchannelsandasupportfeaturethatis:
(a) deactivated for powder-based AM methods; and (b) activated for ME and VP methods.
(a) deactivated for powder-based AM methods; and (b) activated for ME and VP methods.
(a)deactivatedforpowder-basedAMmethods;and(b)activatedforMEandVPmethods.
4.3. Parametric RFID Systems
4.3. Parametric RFID Systems
4.3. ParametricRFIDSystems
For the purpose of this study, HF and UHF RFID systems, presented in Figures 4 and 7, were
For the purpose of this study, HF and UHF RFID systems, presented in Figures 4 and 7, were
Forthepurposeofthisstudy,HFandUHFRFIDsystems,presentedinFigures4and7,were
used for identifying and tracing additively manufactured implants. The operational frequency of the
used for identifying and tracing additively manufactured implants. The operational frequency of the
used for identifying and tracing additively manufactured implants. The operational frequency
HF transponder was 13.56 MHz while it ranged from 864 to 868 MHz for the UHF transponder. The
HF transponder was 13.56 MHz while it ranged from 864 to 868 MHz for the UHF transponder. The
of the HF transponder was 13.56 MHz while it ranged from 864 to 868 MHz for the UHF
HF transponder consisted of 1000 bits of user memory that allowed for 125 ASCII characters for
HF transponder consisted of 1000 bits of user memory that allowed for 125 ASCII characters for
transponder. TheHFtransponderconsistedof1000bitsofusermemorythatallowedfor125ASCII
patient-specific information. Similarly, the UHF transponder had 512 bits for 64 ASCII characters.
patient-specific information. Similarly, the UHF transponder had 512 bits for 64 ASCII characters.
charactersforpatient-specificinformation. Similarly,theUHFtransponderhad512bitsfor64ASCII
The UHF transponder consisted of lower user memory than HF. However, it had a longer
The UHF transponder consisted of lower user memory than HF. However, it had a longer
characters. TheUHFtransponderconsistedoflowerusermemorythanHF.However,ithadalonger
communication range. A parametric model of UHF RFID cavity was custom-designed using Creo
communication range. A parametric model of UHF RFID cavity was custom-designed using Creo
communicationrange. AparametricmodelofUHFRFIDcavitywascustom-designedusingCreo
Parametric (3.0, PTC, Needham, MA, USA) that allows for five input parameters, as shown in the
Parametric (3.0, PTC, Needham, MA, USA) that allows for five input parameters, as shown in the
Parametric(3.0, PTC,Needham, MA,USA)thatallowsforfiveinputparameters, asshowninthe
activity diagram in Figure 8. Similarly to the parametric drug delivery model, it also contains a
activity diagram in Figure 8. Similarly to the parametric drug delivery model, it also contains a
activitydiagraminFigure8.Similarlytotheparametricdrugdeliverymodel,italsocontainsasupport
support feature that removes the automatic support structures of the printer-associated software. The
support feature that removes the automatic support structures of the printer-associated software. The
featurethatremovestheautomaticsupportstructuresoftheprinter-associatedsoftware. Thestatus
status of this feature for different AM methods can be seen in Figure 9. When recreated with the
status of this feature for different AM methods can be seen in Figure 9. When recreated with the
ofthisfeaturefordifferentAMmethodscanbeseeninFigure9. Whenrecreatedwiththecorrect
correct input parameters, the top height (z-axis) of the model, shown in Figure 9a, was aligned with
correct input parameters, the top height (z-axis) of the model, shown in Figure 9a, was aligned with
inputparameters,thetopheight(z-axis)ofthemodel,showninFigure9a,wasalignedwiththetop
the top height (z-axis) of the drug delivery system, shown in Figure 6a, and inserted into the implant
the top height (z-axis) of the drug delivery system, shown in Figure 6a, and inserted into the implant
height(z-axis)ofthedrugdeliverysystem,showninFigure6a,andinsertedintotheimplantdigitally.
digitally. Subsequently, a Boolean subtraction was performed to form its cavity into the implant.
digitally. Subsequently, a Boolean subtraction was performed to form its cavity into the implant.
Subsequently,aBooleansubtractionwasperformedtoformitscavityintotheimplant.

Figure 7. UHF radiofrequency identification transponder conferring to ISO18000-6C.
FFiigguurree 77.. UUHHFF rraaddiiooffrreeqquueennccyy iiddeennttiifificcaattiioonn ttrraannssppoonnddeerr ccoonnffeerrrriinngg ttoo IISSOO1188000000--66CC..
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Figure 8. Activity diagram of a parametric RFID system consisting of five design-based input parameters.
Figure8.ActivitydiagramofaparametricRFIDsystemconsistingoffivedesign-basedinputparameters.