# Digital Drugs

Tony Cornford, Valentina Lichtner

► To cite this version:

Tony Cornford, Valentina Lichtner. Digital Drugs. 5th Working Conference on Information Systems and Organizations (ISO), Dec 2014, Auckland, New Zealand. pp.149-162, 10.1007/978-3-662-45708-5_10. hal-01331822

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Digital Drugs:
An Anatomy of New Medicines

Tony Cornford<fnref n="1" /> and Valentina Lichtner²

¹Department of Management, London School of Economics and Political Science, London, UK
t.cornford@lse.ac.uk

²Decision Making Research Group, School of Healthcare, University of Leeds, Leeds, UK
v.lichtner@leeds.ac.uk

**Abstract.** Medicines are digitalized as aspects of their regulation and use are embodied in or draw from interlinked computerized systems and databases. This paper considers how this development changes the delivery of health care, the pharma industry, and regulatory and professional structures, as it reconfigures the material character of drugs themselves. It draws on the concept of assemblage in presenting a theory-based analysis that explores digital drugs’ ontological status including how they embody benefit and value. The paper addresses three interconnected domains – that of use of drugs (practice), of research (epistemology) and of regulation (structures).

**Keywords:** pharmaceutical preparations · individualized medicine · digital drugs · healthcare · assemblage

# 1 Introduction

Anatomy: 1. *The art of studying the different parts of any organized body, to discover their situation, structure, and economy; dissection.*
[...] 4. *The act of dividing anything, corporeal or intellectual, for the purpose of examining its parts; analysis; as, the anatomy of a discourse.*
(http://en.wiktionary.org/wiki/anatomy)

Medicines<fnref n="1" /> and the ways we use and regulate them are changing, transformed by digitalization [1]. This reconfiguration is associated with visions of scientific, therapeutic,

<footnote n="1">¹ In this paper we use the word medicines and drugs almost as synonyms. We recognise however that they offer slight but significant shifts of emphasis. ‘Medicine’ evokes the practice of medicine and hence the practices of medicines, while drug evokes the manufactured product and its chemical character/materiality. Thus in this most basic sense the thing we address has an inherent multiplicity. The US National Library of Medicine thesaurus (MeSH – Medical Subject Heading) avoids this tension in its own way using the term Pharmaceutical Preparations – “Drugs intended for human or veterinary use, presented in their finished dosage form” (NLM - Medical Subject Headings - 2014 - Unique ID D004364 -</footnote>
managerial and financial breakthroughs from ‘better’ medicines and in particular ‘bet-
ter’ digitally mediated medicine use practices. Expectations include: help in meeting
the needs of aging populations with multiple chronic diseases, the targeting of medi-
cines to individuals (personalization) to significantly increase efficacy and reduce over-
all cost, and computerized clinical decision support that can reduce the burden of harm
caused by adverse drug events (ADEs). The pharma industry too is reconfiguring as it
faces increasing competition from ‘generics’, reductions in the pipeline of new medi-
cines entering the market and the ‘patent cliff’ off which large pharma companies fear
to fall [2, 3]. Such pressures spur changes in how current drugs are marketed, distrib-
uted and paid for [4]. Pharmaceutical business models are realigned to build new rela-
tions between patients, health care institutions and the pharma industry, with drug prod-
ucts enmeshed in or recast as a set of services, and with payment (pricing/reimburse-
ment) shifting from the ‘product’ to outcomes.

The digitalization of medicines is reflected in a number of overlapping areas of con-
temporary research and development including *electronic prescribing*, *stratified medi-
cine*, *personalized medicine*, *smart drug platforms*, *medical profiling*, *pharmacovigi-
lance*, *value based pricing* and *pharmacogenomics* (Table 1). The specifics of the
‘breakthrough’ vision vary, as do the digital mechanisms and resources that are imag-
ined or deployed, but taken overall these initiatives seem to offer new possibilities for
therapeutic improvement and innovation through digitally mediated ways of using
drugs. We believe they also foreshadow multiple possible changes in broader medical
practices, institutional structures, value chains and business models.

This paper presents a theory-based view of what we term *digital drugs*, including
how they embody benefit or value. The work is part of the scoping of a RCUK funded
project addressing how, why and with what consequence medicines are digitalized. In
contrast to the established view of medicines as artefacts located in a stage-based model
of linear progression from drug development, through innovation and testing to ap-
proval and clinical use [5] this work sees drugs as constituted ‘in-use’[6], as performed,
and with their agency located and expressed within and as connections among soci-
technical and economic contexts. In the wider project we ask three primary questions:
1) what is a digital drug - exploring the conceptual and analytical shift from physi-
cal/chemical artefacts towards some digital sociomateriality; 2) how use-practices,
markets and business models evolve for semi-configured and servitized kinds of med-
icines; 3) consequences for/changes in the ‘wider whole’ and the relations between the
parts/players (pharma and health industries, payers, research, regulatory practices, pa-
tient-doctor relations, etc.). Cutting across these areas are multiple questions of value:
therapeutic value, clinical value, health enhancement, value as management of risk or
reduction of harm, market value, value in exchange, value in use, value for money, and
ethical values.

http://www.nlm.nih.gov/cgi/mesh/2014/MB_cgi?mode=&term=Pharmaceutical+Preparation
s&field=entry – Accessed 15 Sept 2014).
<table><caption>**Table 1.** A sample of contemporary digital hybrids in medicines use</caption><thead><tr><td>Concept</td><td>Definitions</td><td>Digital mechanisms</td></tr></thead><tbody><tr><td>Electronic prescribing (EP)</td><td>"The utilisation of electronic systems to facilitate and enhance the communication of a prescription or medicine order, aiding the choice, administration and supply of a medicine through knowledge and decision support and providing a robust audit trail for the entire medicines use process." (Connecting for Health, quoted in [7])<br>On DSS, see also: [8]. For an example of the application of DSS and EP in personalized medicine see: [9]</td><td>Decision support; error reduction; contributing to electronic patient record and Big Data repositories.</td></tr><tr><td>Stratified medicine (SM)</td><td>"Refers to the targeting of treatments (including pharmacological and non-pharmacological interventions) according to the biological or risk characteristics shared by subgroups of patients." [10]<br>See also: [11]<br>Often combined with, or used as synonym for Personalized medicine (PM)</td><td>"Targeting therapy and making the best decisions for groups of similar patients"; finding those who benefit most (or face greater risk), finding those who respond to this treatment.</td></tr><tr><td>Personalized medicine (PM)</td><td>"An emerging practice of medicine that uses an individual's genetic profile to guide decisions made in regard to the prevention, diagnosis, and treatment of disease. Knowledge of a patient's genetic profile can help doctors select the proper medication or therapy and administer it using the proper dose or regime" (National Human Genome Research Institute, cited in [8]).<br>See also: [12]</td><td>Targeting therapy and making the best decisions for a specific patient, on the basis of how the body will respond to treatment; selecting the right/best therapy on the basis of the patient's 'omics' and expected response to active ingredient(s).</td></tr><tr><td>Smart Drug Platforms (SDP)</td><td>"The same pharmaceuticals you take today, with one small change: each pill [contains] a tiny sensor that can communicate, via a digital health feedback system, vital information about medication-taking behaviors and body's response" (paraphrased from [13]). Also seen in wearable devices often linked to mobile phone e.g. Apple HealthKit.</td><td>Smart pills, smart patches (e.g. [14]).<br>Devices and platforms for data acquisition and analysis. Tight feedback on medicines as released in the body.</td></tr><tr><td>Medical profiling (MP)</td><td>The process of determining a patient's 'omics' (a person's characteristics in terms of molecular components and biological pathways, such as genes, transcriptomic, proteomic, metabolomic, and autoantibody) for purposes of PM or SM [15]. See also: [16]</td><td>Informing SM categorizations and PM therapeutic decisions.</td></tr></tbody></table>
<table><thead><tr><th></th><th></th><th></th></tr></thead><tbody><tr><td>Value based pricing (VBP)</td><td>Payment to drug suppliers on the basis of the therapeutic benefit achieved. [35, 36]</td><td>Linking outcome data at patient level to payment; rebalance risk/reward</td></tr><tr><td>Pharmaco-vigilance (PV)</td><td>The assessment of the public health importance of potential new signals found in medicines-use data (e.g. adverse drug reactions) and the confirmation and quantification of risks identified and risk minimization measures (paraphrased from [17]). For an example of use of digital sources (e.g. social media) for this purpose, see [18]</td><td>Adverse event reporting systems, population scale outcomes data via EHR; prospective analysis.</td></tr><tr><td>Pharmaco-genetics (PG)</td><td>“Examines inherited or acquired variations in genes that dictate drug response, disposition, or toxicity and explores how these variations can be used to optimize medication therapy.” [19] Similar to PM and MP, but specific to genetic profile and pharmaceutical therapy.</td><td>Genomics and genomic profiling; epidemiological resources.</td></tr><tr><td>Anti-counter-feiting (AC)</td><td>Falsified medicines are fake medicines that pass themselves off as real, authorized medicines. Falsified medicines may: contain ingredients of low quality or in the wrong doses; be deliberately and fraudulently mislabeled with respect to their identity or source; have fake packaging, the wrong ingredients, or low levels of the active ingredients (paraphrased from European Medicines Agency web site). See also: [20]</td><td>Supply chain integration (bar codes, security codes; tamper proof packaging); consumer services (website seals/logos) and digital services.</td></tr></tbody></table>

## 2 Origins and Character of Digital Drugs

Medicines have always been hybrids (actor networks) - in part biochemical actor (active molecule(s)), in part material delivery system (pill, infusion, suppository, box, leaflet, cold chain), in part informational resources (representations and scripts to validate therapeutics and designate safe and appropriate use). And all bound up with complex and diverse social, scientific and economic interests and practices. However, the examples in Table 1 suggest that contemporary medicines in use become more materially, informationally and algorithmically complex, e.g. more digitally potent. We identify these as digital drugs<fnref n="2" /> – that is:

<footnote n="2">² There is a possibility that something like a clinical medicine might emerge and be administered in a form that is essentially a pure digital phenomenon, e.g. an abstract ‘program’ of biochemical action to be compiled, ‘downloaded’ and ‘run’ in the body. More simply, a therapy such as a gym routine might be seen this way. For example the UK NHS ‘Couch to 5K’ is a therapy embodied in podcast downloads for achieving basic fitness through running [21]. A Google search of ‘digital drugs’ will also give information on possible audio-based psycho-tropic recreational drugs – so called ‘digital highs’. In the sense that music can change your mood, perhaps even suppress pain, this is plausible. However, the general professional opinion is that the technology of ‘binaural beats’ is an interesting sensory phenomenon but psychotropically ineffective and that those who do get high are experiencing at best a placebo effect [22].</footnote>
drugs that are both dependent on and substantially constituted by
multiple digital representations and connections, and whose use and
effectiveness is strongly mediated through digital means.

The lens we use to study digital drugs is assemblage [23] – drugs as performed bundles of artefacts, interests and practices that connect and interact with wider wholes, including clinical work (use), research practices that validate utility/value and mitigate/metricate risk (clinical trials, systematic reviews, pharmacovigilance) and regulatory frameworks to guide practice (regulations, protocols and guidelines).

In using the concept of assemblage we follow the broadly Deleuzian approach [23, 24]. Assemblage signifies digital drugs as events and conjunctions in time and sources of qualitative difference (something happening, some things entangled, something noticed, something different, a process or processes at work, an enactment). In the Deleuzian vocabulary an assemblage is rhizomic, a question of emergence (emergent properties, generativity) in open systems – “the always-emergent conditions of the present” [23]. An assemblage is not then a ‘thing’ (as in a network), with specific life-span or essence. Rather, assemblage is understood in a metaphysics in which “the concept of multiplicity replaces that of substance, event replaces essence and virtuality replaces possibility” [25]. This implies actions and performance of complex and multiple causality/functional interdependencies (e.g. as a medicine is found in a body or bodies, modeled in a genomic profile, supplied, or prescribed), and is not tied to a fixed format or a single unambiguous event or outcome. This is in contrast to the term *hybrid* used here to refer to the (digital) drug as artefact and actor, including its mix of material/digital resources and its evolved sociomaterial agency. We might say that *assemblage* is a concept applied to the ‘instantiation’ of the drug hybrid in use – the ‘here and now’ in a context (including in virtual contexts and in simulations).

We approach digital drugs by opposing the concept to its non-digital or pre-digital i.e. analogue version. The generations of medicines within our established regulatory structures, including the post-Thalidomide medicines, are essentially *analogue drugs* – seen as organic artefacts operating in an organic world of the body. Norbert Wiener, commenting on the probabilistic world of quantum mechanics, notes “the recognition of a fundamental element of chance in the texture of the universe” [26, p. 11]. In this sense anything analogue/organic is incomplete and uncertain (“...this random element, this organic incompleteness” [26, p. 11]). This ‘incompleteness’ certainly applies to medicines and their use. We are used to (or resigned to) the ‘quantum’ effect in medicines even as we strive for a stronger and stronger evidence base and thus certainty. Indeed the quantum is rather large given that most drugs prescribed to people do not work as desired most of the time<fnref n="3" />. Contemporary moves to digitize medicines may be

<footnote n="3">³ The average NNT (Number Needed to Treat) for a licensed drug used in secondary care is well over 5, and for a prophylactic drug (e.g. aspirin for prevention of stroke) it may be well over 1000; that is over 1000 persons need to receive the drug, including paying for it and suffering possible side effects, for one to obtain a therapeutic benefit [27]. As a point of contrast everyday paracetamol (acetaminophen) which a dentist may give you after an extraction has an NNT of around 4.5 for post-operative pain [28].</footnote>
seen as an attempt at closing down ‘this organic incompleteness’ within a digital cer-
tainty – e.g. through stratified medicine, genomics etc. as well as anti-counterfeiting
systems or pharmacovigilance. It is tempting to imagine, as some proponents of these
approaches do, that the shift to digital will drive down the quantum effect as it opens
access to mechanisms that can validate actions and reduce error terms by orders of
magnitude. This is not our position. Through the concept of assemblage, we argue, the
quantum of the digital is made apparent, seen for example, in the simulated or more
generally in the multiplicities that digital ontology accommodates.

Yoo’s definition of digitalization recognizes this transition from analog to digital as
fundamental: “the encoding of analog information into a digital format and the possible
subsequent reconfigurations of the socio-technical context of production and consump-
tion of [the associated] products and services” [29, p. 137]. He proposes that such dig-
italization occurs in various ways: at the level of a physical object (e.g. a digital infusion
pump in place of an analog gravity infusion roller clamp; a 3D tamper proof bar code
on a package), at the level of digital/digitally mediated routines (a digital algorithm for
prescribing; a smart phone app to raise adherence to therapy), or as new representations
(a genomic account of personalized efficacy; a digital information resource on drug-
drug interactions driven by massive electronic health records databases).

Any division between a digital drug (and digital quantum) and an analogue drug (and organic quantum) is not of course clear cut. Transitions occur over years as existing resources are reconfigured in digital forms and new resources added or retro-fitted. Our argument is, however, that as more of the active work we expect medicines to do (their agency) is (co)located in the digital, as digital resources and mechanisms are added and combined, and as this agency (re-)aligns to specific interests and goals, be they therapeutic, social or economic, then the nature of what a drug is, and how a medicine of medicines is practiced, ‘tips’ and something distinct and new emerges – a different kind of drug, a different set of practices, different assemblages. This in turn implies, we argue, new social, organizational and market structures.

Thus, as Yoo’s definition of digitalization suggests and as assemblage requires, our
interest is not focused ultimately on the digitizing of the information/object or the new
digital routines or new representations, significant though these are – and of course we
do need to consider the specific characteristics of digital products and services (as prod-
ucts/artefacts and as representations/services) and the ‘bit string’ economics that they
obey [30]. But it is the ‘subsequent reconfigurations’ that are foreshadowed as seen in
events and actions that we explore.

3 Three Domains: (In-)Use, Research, Governance

We approach digital drugs as assemblage from the perspective of three traditional do-
mains in which they are by convention ‘assembled’ and within which issues of their
value are addressed. These are the domain of clinical and therapeutic use, the domain
of reflexive enquiry and research (gathering of ‘evidence’, knowing), and the domain
of regulation and governance. These three domains are well established, each with its
own practices and an established role/narrative as how we benefit (or not) from medi-
cines. We do not consider here the biochemical domain, important though it is. These
domains are of course interlinked, and one of the characteristics of medicines digitiza-
tion is that these domains connect more and more e.g. events/assemblages are larger,
stronger, richer, and more dynamic.

3.1 In-Use

As suggested above, digital drugs emerge in part out of efforts to computerize existing medicines use practices (prescribing, supply, administration, adherence, etc.) and in this way ‘digitalize the object’ with consequential ontological changes. Since the turn of the millennium it has been a key ambition of developed country health care policies to computerize prescribing in both primary care and secondary care and specifically to exploit the benefits of clinical decision support systems (CDSS) in helping prescribers select the right medicine for the patient, and to do so on the basis of a (digital) medical record (e.g. providing clinical data including in areas such as allergies), and data on recommended therapeutic strategies, available medicines, cost/cost effectiveness, and the effects of interaction among them (e.g. [31]). Similarly in the administration of medicines to or by patients, technological systems and devices such as smart pill boxes or text alerts are deployed to encourage or enforce adherence and record actual use [32]. Much of this work has necessarily been piecemeal (perhaps better described as ‘targeted’) as specific clinical practices and operational needs have been given computer ‘support’ (prescribing, dispensing, supply, administration, audit, ‘academic detailing’, phamacovigilance, etc.). CDSS are also understood as a necessary technological infrastructure, a necessary representation, without which a widespread application of personalized medicine cannot be contemplated [33], e.g. to enable the use in clinical practice of the 2500 genetic tests now already available [8, 34].

The potential *therapeutic value* and/or *service value* that motivate such projects include improved safety and reduction in errors and harm, more consistency of (good) practice, more efficient operations with less waste, and better documented therapy. In this way initiatives to computerize medicines-use are by convention set against the familiar litany of contemporary existential health care problems: rising health care costs, unacceptable error rates and the harm they cause, demographic change, managing a growing burden of treatable chronic disease. Ambitions of progress in these areas are predicated on the existence of good informational infrastructures that represent valid forms of data (e.g. [35]). Many of these ambitions have not yet been fully met but the quality, coverage and scale of data infrastructures improves over time.

More system-focused policy motives reflect a desire for more *net value* (i.e. more health benefit and less harm) and *value for money* out of budgets for medicines. In the English NHS about 50 million population generate a yearly drugs bill of about £12bn. This leads to a perceived need to exploit digital technologies both to help control this significant line of expenditure and to increase the effectiveness of what is spent in improving health outcomes.
Models of the use of digital drugs and their regulation are founded on ideas of digital
systems for establishing efficacy, expressing protocols and in the realization of individ-
ual patient’s care pathways. This approach to medicines and their use is portrayed as
offering a ‘personalized’ (or stratified) service (or services) wrapped around the medi-
cine. Perhaps most significantly, the personalization process – the process to match
your genetics and medical history, test results and other ‘omics’<fnref n="4" /> to what is known
about medicines and therapy - becomes a separate institutional endeavor. Thus a new
industry of ‘diagnostics’ has emerged (with *economic value*) which serves through de-
vices, tests, data analysis and protocols to control and target therapy choice and therapy
delivery – generating a trajectory of events. This is an arena of practice in which the
balance of business interests and clinical or public health interests is today unclear.
More generally the development of an industry and services for diagnostics can be seen
as an example of a ‘service-dominant logic’ (servitisation) [36] as a drug becomes less
a standard product, and is more performed by a complex set of *value generating ser-
vices* (*value* here being taken in multiple senses of the word; see above). The clinical
utility of the therapeutic intervention (its relevance and usefulness in patient care [37])
“becomes a moving target” as information on its benefits and risks increases for groups
or for individual patients [37]. As part of this, ‘patients’, their bodies and their carers
may (but it is in no way inevitable) become more active participants in therapy, with
their involvement too digitally mediated – a possible reconfiguration of the patient and
their role as actor and information source (e.g. in consultations) to a data source (e.g.
through wireless monitors or smart pills).

The health value a medicine generates, and the ability to identify this, becomes an
open and multiple question – how to find a *value-in-use* (e.g. the model of a market in
services, and in particular digital services). This moves away from traditional ideas of
a *value-in-exchange* (the model of a market for products). This change in perspective
is directly seen in contemporary policy debates as national systems and payers consider
‘value based pricing’– e.g. paying (or not paying) for the therapeutic service (or out-
come), not for the molecule, and using a multi criteria algorithm and feedback to iden-
tify those that pass the value test and those that fail it [38, 39].

## 3.2 Research – Evidence in the Doing

A large armory of methods and techniques are today available to support scientific en-
quiry into medicines biochemical efficacy and other consequences and side effects (e.g.
their validation as safe and effective) including statistical measures of outcomes as in a
controlled trial, and synthetic metrics such as Number Needed to Treat (NNT) and
Number Needed to Harm (NNH). These methods, refined in the past 70 or so years,
underpin the established processes through which a new medicine is developed, tested

<footnote n="4">⁴ Omics: a neologism used to describe a range of scientific fields (proteomics, genomics etc.) studying important biomedical aspects about a patient or patient group for subsequent use in personalised or stratified medicine; used also to refer to a person’s characteristics in terms of molecular components and biological pathways (e.g. transcriptomic, proteomic, metabo-lomic).</footnote>
and then licensed for specific uses. It is also the basis for the primary means by which
a healthcare professional is given guidance on what medicines to use, when and how.
Research findings are synthesized into protocols or guidelines for practitioners based
on clinical data with or without some element of health economics (value for money).

In the UK for example, a national body - the *National Institute for Health and Care Excellence* (NICE) - prepares guidance on drug treatments which balances clinical and therapeutic benefits against cost<fnref n="5" />. Fundamental to this is the use of randomized control trials (RCT) and the types of knowledge that can be derived from trials, both individually and through meta-analysis (e.g. Cochrane reviews). It is in this way that we confidently (i.e. within confidence intervals, given the 'random element and organic incompleteness' of life) assert the therapeutic value and risks of a new medicine for specific conditions and/or subpopulations, or recompute them for older drugs. However clinical trials in their traditional form are increasingly considered unsuitable to obtain the evidence on benefits and risks of medicines tailored to specific individuals – for example a trial now has to assess both the efficacy of the treatment and the efficacy of the diagnostic that underpins the stratification, the co-dependent development of drugs and molecular diagnostics [40]. As Lewis et al. suggest of personalized medicine “[It] forces us to question contemporary biomedical views of evidence, including its generation and use in decision making” [40]. There is thus a new focus on a set of complementary approaches to metricate value generated by medicines as they are to be used and as they are revealed through intensive digitization in the domain of use. Individual patient data collected/entered by clinicians at the point of care, or provided by the patient (now a data source), are aggregated into ‘Big Data’ as a potential basis for a new knowledge. A range of new analytic tools analyze or ‘mine’ these often non-standardized data and sift through the ‘data turmoil’ [41]. Among these analytic resources, for example, are new data-driven approaches to test the relationship between biomarkers and clinical outcomes [42] or for standardizing function instead of components in RCTs of complex interventions [43]. Alternatively, “real-time surveillance of individual patient outcomes” [37] may complement trials and improve evidence and support personalization. Drawing on digital resources, trials and experiments can be set up as “randomized studies embedded in routine care” through the use of electronic patient record databases [41]. Through such means the duration of trials and evidence gathering will shorten, some hope. For example, with an active distributed surveillance system in place “a full-scale observational study to evaluate the association between angioedema and drugs targeting the renin-angiotensin system was designed, conducted, and completed in 11 months” [44]. The perception of the need for such methods and the sense of urgency to exploit new research opportunities can be traced in part to the case of the pain killer and anti-inflammatory drug Vioxx. This medicine was licensed in 1999 and withdrawn in 2004. It took over 3 years and a number of patient deaths (disputed but probably in 6 digits [45]) before the negative side effects were acknowledged by the makers and the drug withdrawn from the US market [46]. The proposition is that, with digitalized

<footnote n="5">⁵ http://www.nice.org.uk/guidance/index.jsp?action=bytreatment&TREATMENTS=Drug+treatments Last accessed 15 September 2014</footnote>
patient records, and an effective and proactive pharmacovigilance system, such a case
could be identified earlier with overall less harm [44].

3.3 Governance and Regulation

Research designs reflecting digitization, as described above, imply significant modifi-
cations to regulatory regimes. Regulators have been among the most active in adapting
to the new world of digital drugs. The FDA, the US regulator, has made many changes
in its processes to accommodate a perceived new urgency in drug approval processes
including a fast-track process for ‘breakthrough therapies’ [47]. There is a somewhat
similar designation of ‘orphan drugs’ in medical areas where patient numbers are small
and investments are unlikely to be made on the usual commercial basis. If and when
medicines are fast tracked (a concept with a history traced back to the early period of
HIV/AIDS), and are expected to have a weaker research provenance at the time of li-
censing, they rely more on digital resources for monitoring of “post marketing safety
and effectiveness” [44]. In such circumstances medicines-in-use data can serve to “raise
or lower the level of concern about the overall risk–benefit profile of particular drugs”,
a capability that is described by the FDA as being transformational for the licensing
process [44]. More generally they acknowledge the ability of these new resources of
data to help fulfil the FDA’s role. In the own words of the FDA, it has “evolved its
regulatory processes in response to – and in anticipation of – scientific developments”
[48], noting how it has responded to personalized medicines and the associated growth
of diagnostic products by, “collaborating in key research, defining and streamlining
regulatory pathways and policies, and applying new knowledge in product reviews”
[48]. Meanwhile, Australia has, arguably, the first national framework to assess per-
sonalized medicine for coverage or reimbursement decisions [49].

As suggested above, digitization and the availability of data generated in clinical
care practices (in-use) and held in national registries, migrate from a pure research
(trial) status to embody more directly various interests including of health care system
managers and the payers, patients and patient groups, and the pharmaceutical industry
[50, 51]. That is, research in both new and old formats, and digitalized and synthesized
prospective data sets become engaged in the systems of governance and regulation that
surround medicines use. Research data thus will directly feed the development of de-
tailed and comprehensive protocols of use (and non-use) for powerful and expensive
drugs, described as frameworks for ‘appropriate medicines use’ [50]. Niezen et al. re-
port research in The Netherlands on registries (national databases of medicines use for
a specific class of patient) as digital artifacts that are both an object to be managed, and
an instrument to manage with. In this way clinical work (using medicines with patients
and feeding the registry) and regulatory work (setting the protocol guidelines and reim-
bursement rules) become closely co-constitutive and co-evolving. In their analysis they
question the desirability of a regulatory system that pursues a new ‘digital objectivity’
where available data embodies truth – as seen in many Big Data endorsements, and
captured in the idea of the ‘death of the denominator’ when n=All (see also [52]). They
contrast such digital objectivity with the more established ‘regulatory objectivity’, the
kind of knowledge that is based on multiple evidential resources and embodies conven-
tions and trade offs and collective expertise [53, 54].

4 Conclusion

In this paper we introduce the new concept of *digital drugs* as the intensified integration
of digital services, data resources and algorithms into the practices of medicines. We
anatomize it to reveal some of the main components (use, regulation, research) and
mechanisms and relations using the lens of assemblage. The digitalization efforts that
characterize the movement towards digital drugs are for the most part undertaken in the
name of understanding, best practice, precision, and certainty. The individual initiatives
and innovations described here can be seen individually as the expression of some reg-
ular and rational plan or policy to enhance the efficacy and efficiency of health care.
Our view, our conceptual repertoire, and our chosen lens of assemblage, however, sug-
gest something else or at least a different account of motivations and mechanism. As
proposed here, digitization (digital mediation of drugs) is pursued as a means to address
the organic quantum of chemicals in the body. However, the complexity and multiplic-
ity of elements that converge in or constitute a digital drug and its ‘use/reuse’ suggest
that it need not, and perhaps should not, be seen as a pursuit of a certain or specific
outcomes. Digital drugs are manifest as diverse, distributed, cumulated and dissected
events and incidents across and between domains. They also permit multiple outcomes
as data resources grow, algorithms learn and reconfigure, and virtual phenomena take
new roles. Such multiplicity and instability is a price paid for the desired outcomes, for
example in the case of in-use experimental designs or big data driven protocols (digital
objectivity).

Markus and Saka introduce assemblage as a technique of collage and “something
that generates enduring puzzles about ‘process’ and ‘relationship’” and “[offers] an
odd, irregular and time-limited object for contemplation” [23]. Applying it in these
terms to medicines, this paper raises issues that might be assessed against a wider un-
derstanding of digitalization.

First, is the idea of digital drugs themselves, or more generally of movement (re-
configurations) towards a digital materiality that attaches to and ‘takes over’ classes of
artifacts. In this it recasts them ontologically away from an artefactual existence to one
of assemblage - found in a complex ecosystem of data, algorithm and temporally un-
stable conjunctions, actual, real, virtual or simulated.

Second, and embedded within this perspective, is the question of the 'mechanisms'
of the digital as rational processes of improvement, as (digital) controllers, as sense-
making, and as generative forces. Our case, and the examples in Table 1, suggests that
there is opportunity here for useful fundamental categorizations of this digital agency
through artefactual and assemblage conceptualizations.

Third and finally, is the question of knowledge processes (research designs) as em-
bedded in these phenomena. The methodological arsenal of the evidence based com-
munity (that of innovators, regulators and evidence-based practice) is changing and
adapting. Event and transaction are at the core, able to be inspected, accumulated and
animated in ways that were not possible in earlier eras. This reconfiguration is core to
the phenomena of interest. But can the IS community reconfigure its research agendas
and methods to meet this challenge?

**Acknowledgements.** We would like to thank the colleagues with whom we have discussed various ideas and aspects of this work and the anonymous reviewers who offered insightful comments on a previous version of this paper. We also acknowledge the research grant EP/L021188/1 (2014-2016) awarded by the Research Councils UK Digital Economy Theme to support this work.

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