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Abstract

Many of the most commonly used drugs precede techniques for target identification and drug specificity and were developed on the basis of efficacy and safety, an approach referred to as classical pharmacology and, more recently, phenotypic drug discovery. Although substantial gains have been made during the period of focus on target-based approaches, particularly in oncology, these approaches have suffered a high overall failure rate and lower productivity in terms of new drugs when compared with phenotypic approaches. This review considers the importance of target identity and biology in clinical practice from the prescriber’s viewpoint. In evaluating influences on prescribing behavior, studies suggest that target identity and mechanism of action are not significant factors in drug choice. Rather, patients and providers consistently value efficacy, safety, and tolerability. Similarly, the Food and Drug Administration requires evidence of safety and efficacy for new drugs but does not require knowledge of drug target identity or target biology. Prescribers do favor drugs with novel mechanisms, but this preference is limited to diseases for which treatments are either not available or suboptimal. Thus, while understanding of drug target and target biology is important from a scientific perspective, it is not particularly important to prescribers, who prioritize efficacy and safety.

Keywords

phenotypic drug discovery clinical prescribing mechanism of action drug target

Phenotypic and Target-Based Drug Discovery

The modern, target-centric approach to drug discovery has inherent appeal due to its clear logic—a drug acts upon a target, disease-related protein and thereby alters the disease-related biology driven by the target.¹ In this paradigm, the study of disease biology is also the study and identification of potential therapeutic targets and provides information, via understanding of target proteins, of the mechanism of action of drugs specifically targeting these proteins. Furthermore, the study and identification of individual targets as points of intervention in disease-related networks developed in parallel with molecular biology, and later genomics and proteomics, which together provide a large, near-complete universe of potential proteins as drug targets.² These developments, along with advancements in structural biology, medicinal chemistry, and high-throughput screening, should have provided both tools and substrate to allow successful target-based drug discovery.

One example of the successful application of the target-based approach is imatinib, the first inhibitor of the Abl kinase, developed and approved for Philadelphia chromosome chronic myelogenous leukemia (CML).^3,4 Philadelphia chromosome refers to the reciprocal translocation between chromosomes 9 and 22, formally t(9;22)(q34;q11), which results in the development of a BCR-ABL fusion gene, possessing increased ABL kinase activity, which drives transformation of normal cells into cancer cells.^4,5 The lead compound for the development arose from a project at Ciba Geigy (now Novartis) screening for compounds with activity against protein kinase C (PKC). Subsequent medicinal chemistry around that structure led to the identification of the compound that would ultimately be approved for clinical use as imatinib.⁴ Prior to the approval of imatinib, the best available treatment for CML was low-dose interferon alpha plus cytarabine,⁶ which was thus used as the comparator for the International Randomized Study of Interferon and STI571 (IRIS).⁷ Imatinib achieved dramatically higher rates of both major cytogenetic response (MCyR) and complete cytogenetic response (CCyR) than interferon alfa plus cytarabine (imatinib vs IFNa + Cyt-A: MCyR, 87.1% vs 34.7%; CCyR, 76.2% vs 14.5%).⁷ Imatinib was approved in February 2002, based on phase I trial data showing similar dramatic responses in patients who had already failed interferon alfa therapy.⁸ Review of results over time highlights the transformation of CML from a terminal disease to a chronic illness by this drug. In chronic phase CML (CP-CML), which represents more than 90% of new CML cases, 8-year survival was ≤15% before 1983 (treatments: busulfan, hydroxyurea, cytarabine), 42% to 65% from 1983 to 2000 (treatments: interferon alfa–based regimens and salvage with stem cell transplant), and 87% since 2001 (treatments: imatinib and subsequently developed tyrosine kinase inhibitors).⁹ Thus, imatinib exemplifies the potential of target-based drug discovery. Second-generation tyrosine kinase inhibitors (TKIs)—dasatinib, nilotinib, and bosutinib—also acting on BCR-ABL were subsequently developed. Initially, these were approved only for use in imatinib-resistant disease, but subsequently, dasatinib and nilotinib have been approved for first-line use in CP-CML. Recent clinical trials indicate that dasatinib and nilotinib provide more durable responses and are more tolerable than imatinib and are appropriately being used more in initial therapy in CML.^10,11

While some resistance to imatinib does respond to higher-dose imatinib or switching to second-generation TKIs, resistance due to the T315I mutations in the BCR-ABL oncogene is resistant to imatininb, dasatinib, nilotinib, and bosutinib.¹¹ Here, the molecular mechanism of action truly became relevant, as discovery of the biophysical mechanisms of resistance conferred by the T315I mutation allowed the subsequent development of ponatinib, a third-generation TKI. While it is worth noting that other strategies attempting to take advantage of the structural differences between wild-type and T315I BCR-ABL have failed, ponatinib was designed specifically to remove an interaction between the mutant threonine and the previously developed first- and second-generation TKIs.^12,13 As a result, ponatinib has shown efficacy in all reported BCR-ABL mutations conferring resistance to the earlier TKIs.^11,14 More important from a clinical standpoint, it showed efficacy similar to earlier generation TKIs for non-T315I patients but, more important, was also effective in patients with the T315I mutation.¹⁵ Accordingly, the Food and Drug Administration (FDA) approved ponatinib on December 14, 2012, under accelerated approval, based on phase I and II studies. Taken together, the development of imatinib and subsequent TKIs, particularly ponatinib, to deal with the emergence of imatinib-resistant CML represents an exemplar for target-based drug discovery, not only highlighting the importance of target identity and biology to the development of a new class of therapies for a disease but also demonstrating the utility of structural biology and medicinal chemistry in developing new drugs to combat resistant disease.

While imatinib and other successes of target-based drug discovery are impressive, target-based drug discovery has been less successful than the clarity of the theory or success of imatinib would predict. An analysis of new drugs approved between 1999 and 2008 by Swinney and Anthony¹⁶ found that most were discovered by phenotypic screening, despite the focus on target-based approaches during the period studied. They conclude that the “target-centric approach may contribute to the current high attrition rates and low productivity in pharmaceutical research and development.”¹⁶ In contrast to target-based screening, phenotypic screening refers to the screening of potential drugs based on measures of phenotype, which can be driven by any combination of direct and indirect effects on any number of potential targets, yielding an aggregate effect on the phenotype.

Understandably, the differences between these two approaches are the topic of significant discussion among pharmaceutical researchers, and there appear to be advantages and disadvantages to both approaches. One key difference is the directionality of discovery. In target-centric approaches, also referred to as reverse pharmacology, disease- or process-specific target proteins are identified and prioritized, and subsequent discovery and development yield drugs targeting a specific protein target.^1,17 Observed drug effects are assumed to result from activity on the target, as the process of target identification and validation has identified it as a critical mediator of the disease process. Assessment and design efforts for specificity and selectivity are thus focused on preventing drug action on related proteins (i.e., kinase selectivity for a kinase inhibitor, cross-reactivity for a specific antibody, etc.).¹⁷

This is in contrast to phenotypic drug discovery, or classical pharmacology, in which a drug is found to have activity on a phenotype of interest, which is then further studied for clinical potential, chiefly in terms of safety and efficacy. The drug’s target or targets, as well as the mechanisms by which manipulation of said targets creates a specific, clinically beneficial response, are identified thereafter, if possible.¹ In this paradigm, mechanism of action can progress from unknown, to partial or limited understanding, to target identification and a complete understanding of how the drug exerts the observed, desired effect on phenotype. As no a priori information is available about observed side effects or reasons for efficacy, these parameters must be objectively assessed, and entry of a drug into the clinic would be based on an acceptable clinical risk/benefit profile.

An example of such a drug is aspirin. First marketed in 1899, and found as science developed to have anti-inflammatory and analgesic properties, its mechanism of action was not identified until 1971, when Vane discovered that aspirin blocked the formation of prostaglandins.¹⁸ Cyclooxygenase was identified shortly thereafter and found to be the target of aspirin. However, this was not the end of the story. Subsequent discoveries include the role of cyclooxygenase in platelet function and aspirin’s antiplatelet activity, the discovery of cyclooxygenase 2, and structural studies detailing how aspirin interacts with cyclooxygenase 1.^18–20 At this point, we have the molecular mechanism of action (MMOA) of aspirin, as the MMOA is defined as the biochemical mechanism through which the structural interactions between the drug and its target(s) result in a functional response.¹⁶

Although these differences and their implications are the source of intense debate regarding how drug discovery should be done, a review of the drug discovery literature discloses a curious lack of consideration for the relevance of target identity and biology to clinicians and patients. To aid the reader, the drugs discussed herein are summarized in Table 1.

Table 1.

Clinical Relevance of Target Identity and Biology—Drugs Discussed.

		Target Identity and Biology
Drug	Indication(s)	Target/Drug Type	Relevance to Clinical Use	Impact on Drug Discovery Approach	References
β2-Agonists (i.e., albuterol, salmeterol, formoterol, vilanterol)	Asthma, COPD	β2-Adrenergic receptor agonists	Important; allows prescribers to predict side effects	Identified via classical pharmacology; refined over decades of additional knowledge	^158–163
Inhaled corticosteroids (fluticasone, budesonide, ciclesonide, mometasone, beclomethasone, triamcinolone)	Asthma, COPD	Glucocorticoid receptor agonists	Minimal, clinically used in advance of target identification. Role in asthma therapy based on results of large clinical trials.	Identified via classical pharmacology	^163–166
BCR-ABL tyrosine kinase inhibitors (imatinib, dasatinib, nilotinib, bosutinib, and ponatinib)	BCR-ABL–positive CML	BCR-ABL tyrosine kinase inhibitors	Required for appropriate therapeutic use	Small molecules designed specifically for target	^{3–5,11–15}
Aspirin	Pain, fever, cardiovascular prevention	COX-1 and COX-2 inhibitors	Minimal; clinically used in advance of target identification	Identified via classical pharmacology	^{18–20,167–169}
Bile acid sequestrants (cholestyramine, colestipol, colesevelam)	Cardiovascular prevention, hypercholesterolemia	Bind bile acids in the intestine, preventing cholesterol reabsorption. Other mechanisms incompletely elucidated.	Unclear; published guidelines focus on safety and efficacy	Cholestyramine’s action as a bile acid sequestrant identified via animal experiments; later agents designed specifically to sequester bile acids. Biochemical rather than protein target.	^170–173
Ezetimibe	Cardiovascular prevention, hypercholesterolemia	Blocks cholesterol absorption via NPC1L inhibition	Unclear; published guidelines focus on safety and efficacy	Phenotypic drug discovery. Developed based on metabolic phenotype studies, including phenotypic SAR; target identified in 2005, after approval in 2002.	^174–177
Fibrates (i.e., gemfibrozil, clofibrate, fenofibrate)	Cardiovascular prevention, hypercholesterolemia	Unknown; low-affinity PPARα agonist; also acts on PI3K-AKT; incompletely elucidated	None; still not fully elucidated. Furthermore, published guidelines focus on safety and efficacy.	Identified via classical pharmacology	^178–181
HMG-CoA reductase inhibitors (i.e., atorvastatin, simvastatin, lovastatin, fluvastatin, cerivastatin, rosuvastatin, pitavastatin, pravastatin)	Cardiovascular prevention, hypercholesterolemia	3-Hydroxy-3-methyl-glutaryl-CoA (HMG-CoA) reductase inhibitors	Unclear; published guidelines focus on safety and efficacy	Initial compounds identified in screen of bacterial metabolites; subsequent drugs based on SAR optimization; refined over decades of additional knowledge. Variable pleiotropic effects suggest additional targets.	^{119,129,134,182,183}
Niacin	Cardiovascular Prevention, Hypercholesterolemia	Unknown, acts on DGAT2, GPR109A/B, proposed HDL catabolism receptor, incompletely elucidated.	None, still not fully elucidated. Further, published guidelines focus on safety and efficacy.	Identified as a phenotypic response based on a metabolic hypothesis that was later found to be inaccurate.	^184–187
CETP inhibitors (torcetrapib, evacetrapib, dalcetrapib, anacetrapib)	Cardiovascular prevention, low HDL levels	CETP inhibitor	Not applicable. None yet approved.	Designed specifically for target. Diverse side effects during clinical trials not predictable from target identity.	^{143,144,151,188}
Ivacaftor	Cystic fibrosis in patients with at least one copy of the G551D CFTR gating mutation; under study for other gating mutations	Improves CFTR channel gating; target unknown at time of approval; data suggest direct action on CFTR	No alternative therapies exist; first disease-modifying therapy for cystic fibrosis; requires patient CFTR genotype	Developed using phenotypic screening and assays for CFTR function; built on a foundation of CFTR biology	^106,107,110
α-Glucosidase inhibitors (i.e., acarbose, miglitol)	Diabetes	α-Glucosidase inhibitor	Unclear; published guidelines focus on safety and efficacy	Acarbose activity identified via biochemical screening to identify inhibitors of glucosidases	^189–191
DPP-4 inhibitors (i.e., sitagliptin, saxagliptin, linagliptin, alogliptin)	Diabetes	DPP-4 inhibitors	Unclear; published guidelines focus on safety and efficacy	Small molecules designed specifically for target	^192–194
Meglitinides (i.e., repaglinide, nateglinide)	Diabetes	Closes KATP channel (SURI); increases insulin secretion	Unclear;published guidelines focus on safety and efficacy. Less hypoglycemia with meglitinides than with sulfonylureas by design.	Small molecules developed from sulfonylurea structure evaluated in terms of phenotype, including toxicity	^195,196
Metformin	Diabetes	Unknown; multiple suggested	None; still not fully elucidated	Identified via classical pharmacology	^197–199
Sulfonylureas (i.e., glipizide, glyburide, glimepiride)	Diabetes	Closes KATP channel (SURI); increases insulin secretion	Minimal; clinically used in advance of target identification	Identified via classical pharmacology, due to hypoglycemia in experimental animals	^200–203
Thiazolidinediones (i.e., rosiglitazone, pioglitazone, troglitazone)	Diabetes	PPARγ agonists	Unclear; published guidelines focus on safety and efficacy. Did not allow prediction of side effects.	Identified via classical pharmacology as insulin sensitizers in the early 1980s, starting with ciglitazone; PPARγ identified as target in 1995	^204–210
HCV NS3/4A serine protease inhibitors (i.e., telaprevir, boceprevir, simeprevir, faldaprevir, danoprevir, vaniprevir, asunaprevir, sovaprevir, narlaprevir)	Hepatitis C	HCV NS3/4A serine protease inhibitors	Superior to existing alternatives in terms of safety and efficacy. Relevance of target identity and biology unclear.	Small molecules designed specifically for target	^99,211
HCV NS5A replication complex inhibitor (i.e., daclatasvir, ABT-267, ledipasvir, GSK-2336805, ACH-2928, BMS-824393)	Hepatitis C	HCV NS5A replication complex inhibitor	Superior to existing alternatives in terms of safety and efficacy. Clinical relevance of target identity and biology not yet established.	Daclatasvir was developed without structural information; initial lead (BMS-858) identified via phenotypic screen; target identified via reverse genetics. Others developed after target identified.	^{92,99,101,211}
Nonnucleoside HCV NS5B polymerase inhibitors (i.e., tegobuvir, filibuvir, setrobuvir, deleobuvir, VX-222)	Hepatitis C	HCV NS5B polymerase inhibitor	Not applicable; none yet approved	Designed specifically for target	^99,211–213
Nucleoside HCV NS5B polymerase inhibitors (sofosbuvir, mericitabine)	Hepatitis C	HCV NS5B polymerase inhibitor	Superior to existing alternatives in terms of safety and efficacy. Relevance of target identity and biology unclear.	Designed specifically for target	^{99,211,212,214,215}
Ado-trastuzumab emtansine	HER2-positive breast cancer	Anti-HER2 antibody-cytotoxic drug conjugate	Required for appropriate therapeutic use	Conjugate of nonspecific cytotoxic agent to specific biologic	^79,216
Pertuzumab	HER2-positive breast cancer	HER2-dimerization inhibiting antibody	Required for appropriate therapeutic use	Biologic developed specifically for target	^79,216
Trastuzumab	HER2-positive breast cancer	Anti-HER2 monoclonal antibody	Required for appropriate therapeutic use	Biologic developed specifically for target	^79,216
CCR5 antagonist (i.e., maraviroc, cenicriviroc)	HIV	CCR5 antagonist	Required for appropriate therapeutic use. Use limited by complexity and limitations of screening assay to determine appropriateness of use for any given patient.	Small molecules designed specifically for target	^88,217,218
Enfuvirtide	HIV	HIV fusion inhibitor	Unclear; published guidelines focus on safety and efficacy; tolerability and cost are issues for this agent	Peptide mimetic. HIV inhibitory activity of gp41 peptides was serendipitously discovered during studies for vaccine development. Optimized phenotypically for HIV fusion inhibition.	^219–221
HIV protease inhibitors (i.e., lopinavir, ritonavir, saquinavir, fosamprenavir, indinavir, nelfinavir, atanzavir, darunavir, tipranavir)	HIV	HIV protease	Unclear; published guidelines focus on safety and efficacy. Combination therapy standard; tolerability increasingly important.	Small molecules designed specifically for target	^222,223
Integrase strand transfer inhibitors (i.e., raltegravir, elvitegravir)	HIV	HIV integrase strand transfer inhibitors	Unclear; published guidelines focus on safety and efficacy. Combination therapy standard, tolerability increasingly important.	Small molecules designed specifically for target.	^224–227
Non-Nucleoside Reverse Transcriptase Inhibitors (i.e. tenofovir, efavirenz)	HIV	HIV reverse transcriptase inhibitors	Unclear, published guidelines focus on safety and efficacy. Combination therapy standard; tolerability increasingly important.	Initial lead compounds identified via phenotypic screening to identify compounds inhibiting HIV replication and cytopathicity; approved small-molecule drugs designed to inhibit HIV reverse transcription.	^{213–215,228}
Nucleoside reverse transcriptase inhibitors (i.e., emtricitabine, zidovudine)	HIV	HIV reverse transcriptase inhibitors	Unclear; published guidelines focus on safety and efficacy. Combination therapy standard; tolerability increasingly important.	Small molecules designed to prevent nucleic acid synthesis as a candidate for virus and tumor treatment, failed, found active against HIV in a phenotypic assay. Not designed for HIV reverse transcriptase.	^211,214,215
ACE inhibitors (i.e., captopril, enalapril, lisinopril, fosinopril)	Hypertension	ACE inhibitors	Unclear; published guidelines focus on safety, efficacy, evidence, and patient characteristics	Identified via classical pharmacology. Also enhance kinin B1 and B2 receptor function.	^{178,229–232}
β-Blockers (i.e., propranolol, metoprolol, carvedilol, atenolol, esmolol)	Hypertension	β-Adrenergic receptor blockers	Important; allows prescribers to predict response and side effects	Small molecules designed specifically for target; refined over decades of additional knowledge	^232–236
Calcium channel blockers (i.e., verapamil, amlodipine, nifedipine, diltiazim)	Hypertension	L-type calcium channel antagonists	Unclear; published guidelines focus on safety, efficacy, evidence, and patient characteristics	Identified via classical pharmacology	^232,237
Thiazide diuretics (i.e., hydrochlorothiazide)	Hypertension	Unknown; act on Na/Cl cotransporter to cause diuresis but antihypertensive at nondiuretic doses	None; still not fully elucidated. Furthermore, published guidelines focus on safety, efficacy, evidence, and patient characteristics.	Identified via classical pharmacology in the 1950s in an attempt to make a better carbonic anhydrase inhibitor, a mechanism that is irrelevant to drug activity	^232,238,239
Glatiramer acetate	Multiple sclerosis	Unknown; immunomodulatory effects observed	None, not fully elucidated	Identified serendipitously while looking for encephalitogenic peptides in animal models	^240,241
Interferon β (IFNβ1a, IFNβ1b)	Multiple sclerosis	Recombinant human gene product known to possess antiviral and antitumor properties	Immunomodulatory. Trials based on the incorrect hypothesis that multiple sclerosis results from persistent viral infection, rather than autoimmunity. Despite significant knowledge about interferon biology, mechanism(s) in multiple sclerosis still unclear.	None; recombinant endogenous ligand identified via molecular biology	^{178,240,242–247}
Anti-TNF biologics (infliximab, adalimumab, certolizumab, golimumab, etanercept)	Rheumatoid arthritis, Crohn disease, ulcerative colitis, psoriasis (varies depending on product)	TNF-α	Unclear. TNF levels not used clinically; guidelines focus on multiple factors, including safety and efficacy.	Biologics developed specifically for target	^240,241,247
Cytarabine	Treatment of ALL, AML, and CML as part of multidrug regimens; also approved for treatment of meningeal leukemia. Also antiviral.	Nucleoside analogue; inhibits DNA synthesis; thought to act on DNA polymerase	Unclear; oncology treatment protocols generally include drugs with multiple mechanisms but are ultimately evaluated on clinical outcomes. Not used as an antiviral due to significant toxicities and the availability of less toxic, more effective alternatives.	Semisynthetic nucleoside analogue based on nucleosides found in a marine sponge (Cryptotethya crypta); not specifically designed as a targeted antineoplastic or antiviral. Developed into a drug via classical pharmacology.	^214,248
Interferon α (i.e., Roferon-a, Pegasys)	Treatment of hepatitis C, hairy cell leukemia, Philadelphia chromosome–positive CML within 1 year of diagnosis	Recombinant human gene product known to possess antiviral and antitumor properties	Due to significant toxicities, use is limited to indications lacking other effective therapies	None; recombinant endogenous ligand identified via molecular biology	^{6–8,178,249}
Crizotinib	Treatment of late stage EML4-ALK fusion-positive NSCLC	Designed as a MET inhibitor; also inhibits ALK, EML4-ALK, ROS1, NTRK3, and ETV6-NTRK3	Required for appropriate therapeutic use	Designed for MET kinase; also inhibits ALK and ROS1. Trials planned for MET-positive tumors; ELM4-ALK fusion identified in NSCLC during dose escalation; focus shifted to trials for EML4-ALK–positive NSCLC in late 2007; approved in 2011.	^{145,146,250–253}

ACE, angiotensin-converting enzyme; ALL, acute lymphoblastic leukemia; AML, acute myeloid leukemia; CETP, cholesterol ester transfer protein; CFTR, cystic fibrosis transmembrane conductance regulator; CML, chronic myelogenous leukemia; COPD, chronic obstructive pulmonary disease; COX-1, cyclooxygenase 1; COX-2, cyclooxygenase 2; HCV, hepatitis C virus; HDL, high-density lipoprotein; HIV, human immunodeficiency virus; NSCLC, non–small cell lung cancer; PPAR, peroxisome proliferator-activated receptor; SAR, structure-activity relationship; TNF, tumor necrosis factor.

Relevance of Target Identity and Biology to Clinical Practice

At the outset, it should be clear that to obtain licensure to prescribe medications, one must take courses in pharmacology as a part of their training. Pharmacology is tested on certifying examinations required for licensure, which is a prerequisite for prescribing prescription medications in most countries. While there is significant discussion about the nature of pharmacology training in graduate and postgraduate medical education,^21–24 basic principles are taught during medical school, including the learning of drug names and mechanisms, and applied during graduate medical training and subsequent clinical practice. Similarly, target identity and biology is learned during courses on biochemistry, specific organ system pathology and pathobiology/pathophysiology, immunology, and pharmacology. However, during graduate medical education, the practical outweighs the detailed, and residents focus on the operational aspects of pharmacology—ultimately, which drug for which disease, how much for how long, and, increasingly, which insurance will cover which medication.²⁵ While the American Association of Medical Colleges and other organizations have developed strategies to address issues in pharmacology education,²⁶ the findings below are based on published studies of practicing prescribers.

Thus, while prescribers are knowledgeable in drug target and target biology, consideration of these aspects when selecting drugs appears limited. Specifically, prescribers are more likely to prescribe new drugs only if they have a new mechanism of action and/or novel target (i.e., a first-in-class drug), but only if the existing treatment options are unsatisfactory in terms of safety, efficacy, and/or tolerability.^27,28 Broadly, for all drugs, the most important factors influencing a prescriber’s selection of a given drug are safety and efficacy.^29,30 Other factors include use patterns of peers, subspecialty training, medical school teachers, clinical experience with a drug, and cost.^{27,28,31–35}

However, those findings are based on self-reports from prescribers. When evaluated objectively, prescriber behavior is more complex. Prescribers are significantly influenced by the pharmaceutical industry,^36–38 and this influence alters prescribing patterns and increases costs of therapy.³⁶ The extent of this influence led to conflict of interest policies at medical schools and residency programs, and recent data suggest that these policies, when strictly implemented, reduce the tendency of physicians to prescribe newly marketed drugs over existing alternatives.^39,40 Furthermore, prescribers exhibit other behaviors, including polypharmacy, incorrect or inappropriate drug selection, poor adherence with evidence-based guidelines, and use of expensive drugs despite available effective, lower cost alternatives.^41–44 These have prompted the World Health Organization and others to propose changes in prescription behaviors through improved education, assessment, and technology.^{41–43,45–47} Despite extensive research into prescribing practices, however, there is no evidence that target identity or biology influences drug adoption by providers.

Informal discussions with clinicians identified intermittent consideration of mechanism and a desire to understand drug mechanism both to optimize treatment and avoid adverse events, including interactions. When asked if they would prefer a drug for which mechanism is unknown but is very safe and very efficacious versus one for which the mechanism is known but is less safe and/or efficacious, they chose the drug for which the mechanism is unknown. However, the ideal drug, for all physicians asked, was one that possessed safety, efficacy, and a known target, target biology, and mechanism of action. While clinicians must evaluate their treatment choices based on the expected benefit to their patients, they are also aware of the importance of target identity and biology in selecting the best therapy, as well as its importance in drug discovery. Furthermore, clinicians can often use knowledge of drug target and target biology to predict adverse events (i.e., fatigue is a predictable adverse effect of β-blocker therapy, based on the physiology of the β-adrenergic receptor), allowing us to select an alternate therapy where possible and to counsel our patients regarding these predictable effects, as patient adherence to therapy is greater when they feel that they are fully informed about their treatment (discussed in Efficace et al.⁴⁸).

Also, while individual prescribers may not always consider target identity and biology in treating patients, this may, to some extent, reflect the availability of guidelines for the treatment of many diseases for which multiple classes of drugs are available. For example, guidelines for hypertension, asthma, and diabetes all include discussion of drug mechanisms and targets, to the extent that they are understood. However, when applying these guidelines in routine practice, prescribers likely refer to the therapeutic recommendations in summary form, relying on the considerable expertise of the panel developing the guideline to carry the weight of considering the evidence and science behind the therapies. Thus, while individual prescribers may not extensively consider target identity and biology in daily practice, the use of guidelines provides an avenue for entry of these factors into clinical decision making. However, clinician adherence to diabetes guidelines, for example, is variable, in both the United States and Europe.^49,50 As a result, despite higher costs^51,52 and no evidence of better efficacy,⁵³ initial therapy for diabetes is often not metformin but rather newer, more costly agents including α-glucosidase inhibitors, thiazolidinediones, meglitinides, or dipeptidyl peptidase 4 inhibitors.⁵¹ For the ~35% of patients treated with these newer agents, the cost per year of therapy increases from $232/year to $1354/year, a 483% increase in cost. When newer agents provide therapeutic benefit, cost should appropriately be less important than patient outcomes. However, the use of newer agents solely because of their greater clarity in target identity and biology, without consideration of efficacy, safety, and cost, should appropriately be discouraged. This is perhaps another reason for the overall bias among prescribers for safety and efficacy as key factors driving drug choice when prescribing.

In terms of patient influence on prescribing, there is similarly no published evidence that drug target or mechanism affects patient preference. Rather, evidence suggests a complex and variable set of influences that factor into patient preferences. Studies of patients with multiple sclerosis suggest that adherence to immunomodulatory therapies (interferon β, glatiramer acetate) is related to efficacy and tolerability,^54,55 and while patient information about the disease correlates with adherence, information about the treatment itself does not.⁵⁶ Studies of targeted biologics in rheumatoid arthritis show that efficacy is most important to patients, with safety and tolerability following in importance.^57–59 Furthermore, the clinical equivalence of the anti–tumor necrosis factor (TNF) biologics allows one to identify other influences, such as route of administration, self versus health care provider administration, cost, and frequency of administration. While adherence to these therapies is poor overall, patients on more efficacious treatments are more likely to adhere.^60,61 The problem of adherence exists across all disease areas studied, even diseases such as CML, in which adherence is surprisingly low, despite the risk of CML progression and death observed with nonadherence.^48,62,63 In several studies, the strongest predictor of adherence is once-daily dosing,^64–66 regardless of efficacy. Thus, while adherence and, since it affects adherence, patient preference are essential to the therapeutic success of any drug, there is no indication that target identity or biology affects these decisions, even in chronic diseases where targeted therapies directly affecting disease biology have dramatically improved clinical outcomes.^67,68

Another common perception is that prescribers empirically switch between therapies or combinations of therapies until an optimal treatment plan is found for a given patient. The evidence, on the other hand, suggests that the rate of switching therapies to identify a best treatment is low in hypertension, a common condition for which multiple mechanistic classes of drugs exist.^69–71 In asthma, the evidence suggests that patients prescribed the combination of inhaled corticosteroid and long-acting β-agonist have better clinical responses and lower rates of medication switching than those prescribed inhaled corticosteroid alone or, consistent with importance of ease of administration as a patient factor, long-acting β-agonist and inhaled corticosteroid in separate inhalers.⁷² In type 2 diabetes, combination therapy appears to increase the risk of hypoglycemia, and monotherapy is associated with greater adherence to treatment.⁷³ Thus, the evidence suggests that therapy switching is not common, likely due to the efficacy of first-line drugs for common chronic diseases, the association between switching and nonadherence, and the risk of reducing adherence and efficacy by prescribing multiple medications administered separately.

While the lack of evidence supporting influence of drug target or mechanism of action on patient or prescriber preferences may seem concerning, it is important to consider the goals of the prescriber and patient in making treatment decisions. Although prescribing behavior, as detailed above, is not uniform, it is clear that both patients and prescribers would prefer treatments that are efficacious and safe and, once these conditions are met, are easy to take, tolerable, and affordable. Given this, it has been proposed that prescribers evaluate new drugs in terms of safety, tolerability, efficacy, price, and simplicity (STEPS),⁷⁴ an approach consistent with initiatives for improving prescribing practices for all drugs.^41,42,45,75 Overall, both the stated focus of current prescribers and a major focus of initiatives focused on improving prescribing practices are these nonmechanistic variables, chiefly efficacy and safety.^{41,42,45,46,75,76} Thus, if prescribers are to take drug target and mechanism of action into consideration when selecting drugs, these factors must correlate with efficacy and, ideally, improve safety.

Reasons Safety and Efficacy Should Trump Stated Target Identity and Biology

Target-Based Drug Discovery Has Not Been Applied to Most Diseases

Although target-based drug discovery and development have ushered in the advent of personalized medicine, the use of target-specific therapies tailored to each patient’s disease is limited to a small number of indications, many of which are in oncology.^77,78 Even within oncology, this benefit is limited to a subset of patients. Around 25% of breast cancers are HER2 positive and can thus be treated with biologics targeting HER2⁷⁹ (i.e., trastuzumab, pertuzumab, and the recently approved ado-trastuzumab emtansine), but the remainder and majority would not benefit from HER2-targeted therapy. While imatinib can be used to treat 95% of patients with CML⁴⁹ and has improved their survival to that of the general population,⁸⁰ most targeted therapeutics are limited to subsets of patients within any given disease.

Outside of oncology, target-based drug discovery has led to the development of new drugs in several areas.¹⁶ In infectious diseases, target-based approaches have led to novel therapies for human immunodeficiency virus (HIV), hepatitis C, and influenza. The experience in HIV provides additional insight into the relationship of drug target identity and biology and clinical practice.

For example, although the CCR5 antagonist maraviroc is approved for first-line treatment of HIV, it requires twice-daily dosing and a costly tropism assay prior to use. Furthermore, recent data suggest that deep sequencing improves proper assessment of HIV tropism over the widely used enhanced sensitivity trofile assay (ESTA; Monogram Biosciences),^81–83 which was already an improvement over the tropism assay used in the maraviroc versus efaviRenz in treatment-naive patients (MERIT) trial.⁸⁴ This would add cost and complexity to the use of this drug, and analysis would be complicated by the existence of maraviroc resistance not associated with common mutations.⁸⁵ Due to these factors, and in the absence of data indicating superiority over nonnucleoside reverse transcriptase inhibitor (NNRTI)–based regimens, it is currently not a first-line therapy for treatment-naive patients in either the 2012 Department of Health and Human Services guidelines for adults or children⁸⁶ or the International Antiviral Society–USA Panel.⁸⁷

Cenicriviroc, a new CCR5 antagonist currently in phase II trials, was noninferior at 24 weeks when compared with efavirenz in terms of proportions of patients with undetectable HIV RNA (both with combination NNRTI/nucleoside reverse transcriptase inhibitor tenofovir/emtricitabine) using an intent-to-treat analysis. However, virological nonresponse rates were three times higher in the two cenicriviroc groups (100-mg and 200-mg qd groups; 12% and 14%, respectively) than in the efavirenz group (4%), due to discontinuation by participants. This has been traced to pill burden—only 50-mg pills were available at the time of the trial. “When the study was started, only a 50 mg cenicriviroc pill was available, requiring people to take 2 or 4 cenicriviroc or matching placebo tablets with a meal in the morning, 1 efavirenz tablet or placebo at bedtime, and Truvada whenever desired.”⁸⁸ The manufacturer is aware of this problem and is making higher dose formulations, which should improve adherence and allow the drug’s true potential to be assessed.

Thus, while targeting CCR5 to prevent HIV entry has clear scientific rationale and has been achieved, tolerability, complexity, and cost issues have prevented the broad adoption of CCR5 blockade as a therapy for HIV. Similarly, while the fusion inhibitor enfuvirtide is an elegantly designed biomimetic peptide that prevents HIV from fusing with the target cell, it is only approved for salvage therapy. Furthermore, it has to be injected twice daily⁸⁹ and is very costly. As a result, it has limited use when compared with other antiretrovirals (i.e., protease inhibitors, NNRTIs, integrase strand transfer inhibitors, etc.). It is important to point out that both HIV protease inhibitors and integrase strand transfer inhibitors also represent drugs developed via knowledge of target biology and identity, and that as a whole, HIV treatment represents an area in which understanding of drug target identity and biology is important to defining appropriate treatment combinations.

Similarly, novel therapies approved and in development for hepatitis C promise to revolutionize the treatment of this disease. Specifically, the development of novel NS3/4A serine protease inhibitors telaprevir and boceprevir, NS3 protease inhibitor asunaprevir, NS5A replication complex inhibitors daclatasvir and ledipasvir (GS-5885), and NS5B polymerase inhibitor sofosbuvir provide dramatically improved response rates compared with interferon/ribavirin therapy that has been the standard of care.⁹⁰ Indeed, combinations of these newer drugs provide the potential for the development of interferon-free regimens for the treatment of hepatitis C. This would be a boon for patients, as interferon’s toxicities are significant, including flu-like symptoms and mood disorders, which negatively affect adherence and thus efficacy.⁹¹ Thus, in hepatitis C, target identity and biology will ultimately lead to a revolution in treatment. However, while telaprevir, boceprevir, asunaprevir, and sofosbuvir were discovered using structure-based drug discovery methods or methods that have not yet been disclosed (ledipasvir), daclatasvir was discovered by a phenotypic drug discovery approach.^92,93 Lead optimization was done prior to the identification of the target using chemical genetics.^92,93 Specifically, the initial screening hit, BMS-858, subsequently optimized into BMS-700952 (daclatasvir) without structural information regarding drug binding to target.^94–98 Indeed, the initial hit, BMS-858, was identified through what the discoverers term “a mechanistically unbiased approach based on chemical genetics to identify chemical starting points for interfering with HCV [hepatitis C virus] replication.”⁹² Specifically, they screened compounds against both a HCV viral replicon system and bovine viral diarrhea virus (BVDV) to eliminate nonspecific compounds. Once hits were identified, the investigators analyzed the genomes of resistant viruses as they emerged in culture and, using that information, identified the HCV NS5A protein as the target of BMS-858.⁹² Subsequent to this, during chemical optimization but prior to the availability of structural information, they discovered that symmetry was an important contributor to antiviral activity, and this, along with other structure-activity relationships identified, led to the development of BMS-700952.^93–97 Thus, rather than selecting a target and developing a drug, this case demonstrates the development of a targeted therapeutic that arose from a target agnostic, phenotypic approach. While the development of subsequent generations of NS5A inhibitors will benefit from knowledge of target identity and structural information,^93,99–101 especially in designing drugs to overcome resistance to first-generation NS5A inhibitors, the development of NS5A inhibitors is another example of efficacy rather than target identity driving successful drug discovery.

Despite these advances, it remains that at the present, for the treatment of most patients, target identity and biology are less relevant to treatment selection than safety and efficacy. Furthermore, the properties of novel therapies developed for specific targets can limit their clinical utility. In most cases, target identity does not confer drug safety or efficacy and is appropriately less important than safety and efficacy when viewed in the patient-centric perspective of the prescriber.

Application of Personalized Medicine Does Not Require Knowledge of Drug Target Identity or Mechanism of Action

Recent advances in the treatment of cystic fibrosis provide an example of how personalized medicine can occur without knowing the precise target of a novel therapeutic and can be applied with limited provider understanding of the biology at work. Cystic fibrosis is a fatal genetic disease caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene, which encodes a multifunctional protein whose primary role is as an adenosine triphosphate (ATP)–gated chloride channel essential for normal salt and fluid transport in multiple organs, including the lung.¹⁰² The discovery of the CFTR gene in 1989 prompted the development of therapeutic approaches to restore normal CFTR function, either through replacement of CFTR through gene therapy or by improving the function of the mutant CFTR.¹⁰³ The latter is complicated by the fact that different mutations predictably affect the CFTR protein and its function in different ways.^102,104,105 While the most common CFTR mutation, ΔF508, results in both impaired trafficking to the cell surface and problems with channel gating, other less common mutations, such as G551D, affect only channel gating.^104–106

Using cells expressing mutant CFTR genes, Van Goor and colleagues¹⁰⁶ at Vertex Pharmaceuticals screened 228,000 compounds for compounds that would enhance CFTR function using a cell-based fluorescence membrane potential assay. Specifically, they screened for two types of compounds: CFTR correctors, which improve ΔF508 CFTR trafficking, and CFTR potentiators, which improve ΔF508 CFTR gating at the cell surface. From the CFTR potentiator screen, hit selection and lead optimization yielded ivacaftor (VX-770).¹⁰⁷ It should be noted that while several rounds of analogue synthesis and testing were required to go from the hit VRT-532 to drug VX-770, compounds were strictly assessed for an effect on ion transport in mutant CFTR-expressing cells, rather than CFTR binding or other assays of isolated CFTR protein. While ivacaftor is unable to restore normal CFTR function to cells with the ΔF508 mutant CFTR, due to its dual defects in trafficking and gating, it restores normal CFTR function in cells with G551D, as this mutation only affects gating.¹⁰⁷ For this reason, ivacaftor was moved into clinical trials for the treatment of patients with cystic fibrosis with the G551D mutation and found to improve not only sweat chloride measurements, reflecting the improvement in CFTR function, but also lung function and nutritional status, both important clinical parameters, leading to its approval for the treatment of patients 6 years and older with this mutation in January 2012.¹⁰³

This would represent a triumph for target-based drug discovery had ivacaftor been developed with the CFTR as a target, based on structural studies of the CFTR protein—developing a precise molecular mechanism of action to repair the defects in the mutant channel. Instead, ivacaftor represents the development of a genotype-specific personalized therapeutic using phenotypic drug discovery methods and, as such, provides a counterexample to the widely held assertion that personalized medicine is only possible using the target-based drug discovery approach. Indeed, the exact mechanism by which ivacaftor exerts its beneficial effects on CFTR gating is still unclear, and although recent work suggests direct action on CFTR itself,¹⁰⁸ this was not by design. Phenotypic drug discovery can yield targeted, personalized therapeutics.

That said, had these results been evaluated without comprehending the effect of non-ΔF508 mutations on CFTR function gained through decades of work on understanding this critical target’s biology, both in terms of degree of functional impairment and how each mutation affects the channel, drug development could not have shifted to the treatment of the G551D mutation.^104,105 Similarly, the ongoing development of CFTR corrector compounds, including VX-809, VX-661, and VX-983, with the goal of combining them with the potentiator ivacaftor to improve ΔF508 CFTR channel activity, is also built from this deep understanding of CFTR biology.¹⁰⁹ Last, the idea of using ivacaftor for non-G551D mutations that affect CFTR gating was again based on our understanding of its end target, the CFTR. In vitro experiments have confirmed the ability of ivacaftor to significantly improve the function of CFTR proteins with non-G551D gating mutations.¹¹⁰

Thus, a genotype-specific therapeutic, representing another example of personalized medicine, can be successfully discovered, developed, and brought to market without knowledge of the target or precise mechanism of action, using phenotypic approaches and relying on safety and efficacy to determine suitability for clinical use, consistent with the prescriber preference for safe and effective drugs. Prescribers need only to know the CFTR genotype of the patient to determine whether the drug is appropriate. However, despite the evidence that drug target identity and biology do not significantly factor into prescribing practices, an understanding of disease biology is a prerequisite for the development of novel therapies, regardless of the pharmacology paradigm, classical or reverse, used. Indeed, this has led some to differentiate modern phenotypic drug discovery as different due to the inclusion of information regarding potential targets and known pathobiology¹¹¹ and systems biology and pharmacology,¹¹² while others term this emerging blend of methods an integrated systems-level approach to drug discovery.¹¹³

Stated Target and Mechanism of Action Do Not Always Explain Observed Drug Effects

In the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT), thiazide diuretics were found superior to calcium channel blockers and angiotensin-converting enzyme (ACE) inhibitors as a first-line therapy in hypertension.¹¹⁴ Despite the lack of evidence for improved efficacy or safety over thiazide diuretics and the lower cost of thiazide diuretics, both ACE inhibitors and calcium channel blockers had gained a substantial share of the market for first-line antihypertensive therapy, felt to be due largely to aggressive marketing to prescribers by the pharmaceutical industry.⁴⁴ The superiority of thiazide diuretics over ACE inhibitors and calcium channel blockers again suggests that a specific target and mechanism of action do not predict clinical efficacy or safety, since while the ACE inhibitors and calcium channel blockers have well-defined targets and mechanisms, the mechanisms by which thiazide diuretics exert their antihypertensive effects are still not entirely understood,^115–117 despite their discovery in 1957.¹¹⁸

Another case of discordance between our knowledge of target and mechanism of action and clinical outcomes is the complexity in the relationship between lower serum cholesterol levels and cardiovascular events. It is well established that high cholesterol levels increase risk for cardiovascular events, first observed in the Framingham Heart Study and confirmed in subsequent studies,¹¹⁹ leading to the development of cholesterol-lowering therapies. Early anticholesterol therapies tested included niacin, gemfibrozil, and bile acid sequestrants, which showed some efficacy in reducing both cholesterol levels and cardiovascular risk, strengthening the relationship between cholesterol and heart disease.^120–122 Over the course of nearly 30 years, from the elucidation of the cholesterol biosynthesis pathways to 1987, drugs targeting 3-hydroxy-3-methyl-glutaryl-CoA (HMG-CoA) reductase were developed, culminating in the FDA approval of lovastatin to reduce cardiovascular risk in patients with elevated cholesterol levels,¹¹⁹ followed by the development of several other HMG-CoA reductase inhibitors, collectively termed statins. As evidence for the efficacy of statins in reducing cardiovascular risk continued to accumulate, it appeared that this was a clear case of a specific and potent drug acting on its target, with minimal mechanism-related side effects, resulting in lower cholesterol levels and, in turn, reduced risk of death from cardiovascular events.¹¹⁹ However, other data suggest that the observed benefit of statin therapy may not be related solely to effects on circulating cholesterol levels.

One line of evidence supporting a role for non–lipid-reducing activities of statins in their observed beneficial effects comes from a lack of these effects seen in studies of ezetimibe, a cholesterol absorption inhibitor. In two major trials, the addition of ezetimibe, while lowering cholesterol beyond statin therapy, did not have a significant impact on a surrogate measure for cardiovascular event risk,^123,124 leading to intense debate about the role of ezetimibe in preventing cardiovascular events^120,125 and reduced prescriptions for ezetimibe.¹²⁶ While ezetimibe reduces circulating cholesterol levels, it has not been shown to affect risk for mortality, cardiovascular events, or surrogate end points, suggesting that cholesterol reduction does not fully explain the effects of statins.

Apart from the evidence of non–lipid-lowering activities suggested by studies of ezetimibe, there is substantial clinical and biological evidence that statins have significant activities beyond HMG-CoA reductase inhibition. While outweighed by the overall benefits to cardiovascular risk and mortality, statins appear to increase risk for the development of type 2 diabetes through an unknown mechanism.¹²⁷ Other observed effects of statins include effects on vascular nitric oxide synthesis, inhibition of hepatitis C virus replication, autophagy, angiogenesis, platelet aggregation, inflammation, and immune signaling.^128–131 Some of these effects are thought to be due to activities of statins on RhoA kinase, GTPase isoprenylation, and blockade of the interaction between LFA-1 and ICAM-1, but the biology underlying most of these activities is unknown. Small clinical trials and post hoc analyses of larger trials suggest that statins may be beneficial in asthma, chronic obstructive pulmonary disease, cancer, multiple sclerosis, transplantation, rheumatoid arthritis, osteoporosis, influenza infection, and sepsis.¹²⁹ Studies associating statin use with better outcomes in influenza infection have led some to advocate for clinical trials of statins in the treatment of influenza.^132,133 A report in this issue of the journal on high-throughput screening for enhancers of interferon signaling shows that different statins demonstrate differing ability to enhance interferon signaling and in turn antiviral defense.¹³⁴ This is consistent with a study showing that different statins exert different effects on hepatitis C virus replication,¹²⁸ risk for adverse effects,¹³⁵ diabetes risk,¹³⁶ cardiovascular outcomes,¹³⁷ and biomarkers of lipoprotein oxidation.¹³⁸ Taken together, these data strongly suggest that differences between statins and statin activities in non–lipid-lowering contexts are related to off-target effects.

Thiazide diuretic and statins are only two of many examples of drugs whose effects on patients cannot be fully explained by their stated mechanisms of action or the biology of their intended target. Given results of an analysis of reported drug-protein interactions, the average drug is acknowledged to interact with six targets,¹³⁹ a number that is even more sobering when one considers the fact that drugs are generally only tested on a few targets during discovery and development, due in part to a lack of assays to assess drug binding and/or effect for most proteins. As this is the case, it is unsurprising that widely used drugs have effects that are not explained by action on their primary target, whether that target is identified post hoc in the case of drugs discovered by phenotypic approaches or, as discussed in the next section, is designated a priori for drugs developed using target-based approaches. The fact that this remains true, despite the intense and ongoing efforts to better identify targets for existing drugs and to evaluate drugs in development—in terms of target identity for phenotypic drug discovery or target validation for target-based drug discovery and for off-target activities in both cases^140,141—likely contributes to the focus of prescribers on empirically determined efficacy and safety from the large clinical trials required for approval, as well as postmarketing trials and surveillance, rather than on what evidence and experience suggest is incomplete information regarding target identity and/or biology for any given drug.

Target-Based Drug Discovery Does Not Preclude Off-Target Activities and Resulting Drug Properties and Faces the Risk of Target Failure: Insights from the CETP Inhibitors

While one of the theoretical advantages of targeted drug discovery is a reduction of side effects due to action solely on the target, it is clear from kinase profiling studies of drugs that even “specific” inhibitors have off-target activities.¹⁴² Furthermore, a study of the known interactions between drugs and proteins found that any given drug binds an average of six proteins, including its intended target,¹³⁹ supporting the idea that off-target activities occur due to drug action on proteins from families other than that of the target.¹⁷ Off-target activities are suspected to underlie the high-profile failure of the cholesterol ester transfer protein (CETP) inhibitor torcetrapib,¹⁴³ which, while intended to raise high-density lipoprotein (HDL) to improve cardiovascular risk, resulted in hypertension and increased mortality in a large phase III clinical trial.¹⁴⁴ While this is an undesirable off-target effect, there are cases where off-target effects are beneficial. One such case, recently identified, is that of crizotinib. While crizotinib is FDA approved for the treatment of locally advanced or metastatic non–small cell lung cancer that is positive for anaplastic lymphoma kinase (ALK), its intended target,^145,146 it is also known to act on other kinases, including ABL and MET.¹⁴⁷ Recently, however, it has been shown to inhibit not only NTRK3, an off-target activity that had been identified through kinase profiling,¹⁴⁷ but also the fusion kinase ETV6-NTRK3, which has been implicated in other cancers,¹⁴⁸ including some head and neck cancers,¹⁴⁹ but for which no targeted therapeutic is currently available. Thus, while off-target effects are generally undesirable properties of drugs, especially when the drugs have been developed and are marketed for action on a single protein target, drug promiscuity can yield benefits. The increasing recognition that many safe and effective drugs act on multiple targets to yield desired clinical outcomes, combined with the current challenges faced by target-centric approaches, has led some to propose taking advantage of action on multiple targets, referred to in this context as polypharmacology, in drug discovery and development.^112,150

CETP inhibition highlights another aspect of the challenges facing drug discovery and development—the possibility that even if a safe drug is found for a given target, it may not yield the desired clinical outcomes, despite evidence of target validity from preclinical and epidemiological evaluations, termed target failure for the purposes of this review. This is highlighted by the recent failure of dalcetrapib, another CETP inhibitor that, while safely raising HDL levels, did not affect the frequency of cardiovascular events in a high-risk population.¹⁵¹ While final clarity on the role of CETP inhibition in cardiovascular risk reduction awaits the results of ongoing trials for anacetrapib and evacetrapib, there is concern that raising HDL cholesterol levels may not improve cardiovascular risk as previously thought, highlighting the risk of target failure in target-based drug discovery.¹⁵² As expected, there is substantial discussion in the literature regarding target failure, including assessment of the causes and remedies for observed failure of targets identified through basic science to lead to efficacious drugs,^153,154 leading some to advocate for the use of phenotypic screening to identify novel drug targets.¹⁵⁵

While off-target effects and drug action on multiple targets are undesirable attributes, the success of drug repurposing as a strategy to identify new uses for existing drugs is due in large part to the existence of novel targets and mechanisms for approved therapeutics.^156,157 Taken together, the evidence for off-target activities both beneficial and detrimental of targeted therapeutics, as well as the success of drug repurposing, suggests that our understanding of any given drug’s target and mechanism of action are significantly limited, providing another reason for the observed focus on safety and efficacy of patients and prescribers.

In conclusion, the understanding of disease biology and the identification of specific targets for the development of novel therapeutics are important to the ongoing process of drug discovery and development and should remain so. However, published data suggest that prescribers value safety and efficacy first and foremost when choosing treatments. In considering the reasons for prescriber focus on efficacy and safety over target identity and biology, several important factors emerge. First, as patient outcomes are the primary goal in any drug choice, prescribers are correct in choosing the therapeutic that is most likely to work, both in terms of efficacy in the patient’s illness and, for the patient, in terms of safety, tolerability, and cost. Second, while targeted, individualized therapy is now routine practice in oncology and represents a success of target-based drug discovery, phenotypic approaches can also lead to successful patient-specific drugs, as seen in cystic fibrosis. Third, stated knowledge on drug target and mechanism is often incomplete, inaccurate, or both and, even when correct for some actions of a drug, does not explain all actions of a drug, especially observed differences within a class of drugs acting on the same target. Last, even drugs designed using target-based drug discovery approaches have significant, often unknown off-target effects, both beneficial and detrimental. As this is the case, the idea that a drug’s effects can be predicted on the basis of its target is unlikely to be true in most cases. This suggests that even drugs designed for a specific target should be carefully evaluated for other effects, targets, and mechanisms, much as if the drug had been developed without a specific target, as in classical pharmacology or phenotypic drug discovery, which some have termed neoclassical pharmacology. Ultimately, the role of prescribers is to treat patients and their illnesses, and currently, this role is better served by evaluating drugs in terms of efficacy and safety.

Footnotes

Acknowledgements

I thank Dr. Dhara A. Patel for editorial assistance in preparing the manuscript, as well as the members of the Phenotypic Drug Discovery Special Interest Group of the Society for Laboratory Automation and Screening for insightful discussions.

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author received no financial support for the research, authorship, and/or publication of this article.

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