Thompson, Corbin G. PharmD*; Cohen, Myron S. MD†; Kashuba, Angela D.M. BScPhm, PharmD, DABCP*,†
Antiretroviral therapy (ART) has saved millions of lives and greatly increased the life expectancy of individuals living with HIV.1 The Joint United Nations Programme on HIV/AIDS set a goal of having 15 million individuals living with HIV on ART by 2015, reaffirming that widespread ART implementation is a global priority.2 It is well recognized that these drugs penetrate into the genital tract and decrease viral shedding.3–5 ART, therefore, was postulated to prevent transmission and acquisition of HIV. Indeed, pharmacological interventions aimed at preventing the spread of HIV using currently approved antiretroviral (ARV) medications have shown success in various settings.6–8
Most recently, the successful use of ART for prevention of transmission has focused on the use of these agents to prevent HIV acquisition.9–12 If ART stops replication in an HIV-positive individual and prevents transmission, it is reasonable to think that ART can also prevent transmission in an HIV-negative individual when confronted with a replication-competent founder virus. Accordingly, preexposure prophylaxis (PrEP) using topical or systemic (oral or injectable) ARVs to prevent HIV infection around the time of exposure makes the issue of drug penetration into genital and rectal mucosal tissues critically important. Many factors can affect drug concentrations and the concentration–response relationship in these tissues and not all are fully understood. This review will summarize these factors and propose how they may contribute to achieve protective concentrations and effective dosing strategies for PrEP. We will also address the limitations of the methods currently used to generate these data and suggest ways to improve the applicability of the results.
EVOLUTION OF DRUG CONCENTRATION DATA IN MUCOSAL TISSUES
Evaluation of drug exposure in female genital and in colorectal tissues began in the 1970s. Early publications examined the distribution kinetics of antibiotics in these tissues with the goal of identifying ideal candidates for surgical prophylaxis in gynecologic and colorectal surgery.13 These pharmacokinetic (PK) studies of antibiotic distribution in the surgical setting continued throughout the 1980s.14,15 Additional investigations identified antibiotics that were well suited for the outpatient treatment of gynecologic infections.16–18 Measures of drug exposure in these early studies typically consisted of single concurrent tissue and serum samples obtained after a single dose of antibiotic and were reported as a tissue:plasma ratio. Later studies conducted more rigorous examinations using single- and multiple-dose kinetic data to report tissue:plasma ratios.19–21 Due to different distribution characteristics in tissues compared with plasma, single time point concentration ratios could over- or underestimate true tissue exposure.19 Therefore, a more comprehensive measure of drug exposure in these tissues, the area under the concentration time curve (AUC), was used to calculate tissue:plasma AUC ratios. These early studies made it clear that drug concentrations at sites of action cannot be assumed to be the same as plasma concentration and that the ability of drugs to penetrate into tissue can vary greatly even among members of the same drug class, which may prove quite important in clinical trials.22
Mucosal tissues of the vagina, cervix, and colorectum are a primary target for early HIV infection and replication.23 Simian immunodeficiency virus pathogenesis research in macaques has demonstrated rapid viral penetration into genital and rectal tissues after local inoculation. Viral DNA has been detected in the vaginal epithelium within hours after inoculation, and founder populations of virus can be detected in cervicovaginal tissues as early as 24 hours postinoculation.24–26 Clinical studies have confirmed cervical, vaginal, and colorectal transmissibility of HIV.27–29
Although initial viral populations are small, rapid local and systemic dissemination occur during the first 4 days of infection, making this time period a critical target for pharmacological interventions.24 Therefore, an important determinant in successful PrEP must be the ability of ARVs to achieve and sustain adequate concentrations in the mucosal tissue, whether through topical or systemic administration. To prevent the index infection in the new host, sufficient concentrations of ARVs must be present at the time of exposure and for some yet-to-be-defined length of time afterward. Penetration of ARVs into the colorectum, semen, and tissues of the female genital tract (FGT) has been extensively researched.19,20,30–33 The resulting data have revealed a high degree of variability in penetration, both between and within drug classes.
The penetration profiles for the ARVs are summarized in Figure 1.19–21,30,31,33–42 Oral ARV formulations comprise the majority of penetration data. Generally, the nucleoside/tide reverse transcriptase inhibitors achieve high concentrations in the FGT. Zidovudine (ZDV), emtricitabine (FTC), and lamivudine (3TC) all have single- and multiple-dose tissue:plasma AUC ratios greater than 1.00. Ratios of protease inhibitors and nonnucleoside reverse transcriptase inhibitors (NNRTIs) are more variable, with most protease inhibitors having poor penetration (<0.20) into the FGT and NNRTIs having highly drug-specific penetration. The CCR5 antagonist maraviroc penetrates well into the FGT (AUC ratio 1.9–2.7), whereas the integrase strand transfer inhibitor raltegravir shows moderate penetrative ability (AUC ratio 1.00 in HIV-negative women and 4.00 in HIV-positive women, driven primarily by differential blood plasma exposure).35
There are some inconsistent trends in penetration between single and multiple doses. In the case of efavirenz, stavudine, and atazanavir, the extent of penetration is constant regardless of the number of doses given, reflecting a constant relationship between systemic and local exposure. However, for tenofovir (TFV), abacavir, and lopinavir (LPV), drug exposure declines in the genital tract with repeated dosing. The tissue:plasma AUC ratio declines from 1.1 after a single dose to 0.75 after multiple dosing for TFV, from 0.21 to 0.08 for abacavir and from 0.17 to 0.08 for LPV. This suggests that, with repeated dosing, entry mechanisms for some ARVs either become saturated, upregulated (eg, efflux transporters) or downregulated (eg, uptake transporters), decreasing the ability of these drugs to reach the FGT.
The PK profiles of alternative ARV formulations have also been studied. Topical TFV gel has been successful in preventing HIV infections in clinical trials and achieves favorable tissue concentrations when applied vaginally or rectally as either a gel or a ring.43,44 This formulation has also been shown to rapidly distribute between vaginal and rectal tissue after application to either site, although the exposure in the nondosed site reaches only approximately 5% of the exposure seen at the site of dosing.43 A study in 24 HIV-negative women showed that a vaginal ring formulation of dapivirine achieved cervicovaginal fluid concentrations that were 3 log units higher than plasma concentrations and 4 log units higher than the reported in vitro EC50 of HIV-1LAI.45 Furthermore, a novel NNRTI rilpivirine has shown penetration of AUC ratios of 1.2–1.95 in cervicovaginal fluid and 0.48–1.0 in vaginal tissue when administered as a long-acting injectable formulation.41
FACTORS INFLUENCING DRUG ENTRY INTO TISSUES
The data described above highlight the need to identify the variables affecting mucosal penetration of small molecules. Once these variables are understood, they can be considered in the ARV development process and help identify ideal drug candidates for PrEP.
There are several physicochemical factors that influence tissue penetration: blood perfusion, protein binding, molecular size, lipophilicity, ionization state, and membrane transporter affinity. Adequate tissue blood flow is a necessary requirement for drug efficacy, particularly for drugs that are efficiently metabolized by target organs, also called “high extraction compounds.” For highly extracted drugs, there is a direct relationship between tissue perfusion and drug entry into tissues, and lack of perfusion is a likely contributor to the difficulty of treating infections at certain anatomic sites (eg, central nervous system, bone). One of the primary determinants of pharmacodynamic (PD) efficacy is the fraction of unbound drug available to cross the cellular membranes and enter tissues and cells.46,47 Differential protein binding between 2 similar drugs can have large PD implications. For example, it has been shown that ARVs which are highly protein bound (eg, efavirenz, LPV), have much lower exposure in tissues than those which have less protein binding (eg, FTC, TFV).19 Chemical characteristics can also affect drug entry into tissues and cells, mostly by affecting the ability of a compound to diffuse across cellular membranes. Perhaps the most well-established characteristic is the inverse relationship between the molecular size of a drug and its penetrative capability.46 An additional factor is the lipophilicity of a drug. Highly lipophilic compounds (eg, propranolol) are able to cross the cellular membranes much more easily (and have better intestinal absorption) compared with hydrophilic drugs (eg, hydrochlorothiazide). This is an important consideration in drug development, where formulation changes can occur as a result of poor intestinal absorption. Finally, the ionization state of a compound, which is determined by its pKa, is another element that can aid or hinder diffusion across membranes. Drugs that are mostly ionized at physiological pH (eg, ZDV) are much less likely to enter tissues and cells compared with drugs that are neutral at an identical pH (eg, FTC). It should be noted that although a drug's pKa is unchanging; its ionization state can differ among tissues due to local pH changes. For example, an acidic environment (eg, prostatic fluid; pH 6.6) can cause a drug with a pKa > 6.6 (eg, ZDV; pKa 9.68) to be ionized and trapped.48,49
In addition to physicochemical properties, the effect of transporter expression and differences in transporter affinity among ARVs may play a critical role in determining mucosal penetration. The effect of transporters on ARV uptake and elimination from tissues has been thoroughly evaluated. A review by Kis et al50 summarizes the inhibitory and induction effects of ARVs on the ATP-binding cassette and solute carrier transporter families, which are known to contribute ARV penetration into various tissues and compartments. Briefly, the efflux transporters of the solute carrier family, especially p-glycoprotein (P-gp), are the primary method of cellular efflux for almost all ARVs with the exception of the NNRTIs. Transporters responsible for ARV uptake are more varied but are generally comprised the organic anion transporters. Importantly, all ARVs with the exception of raltegravir inhibit and/or induce one or more of these transporters to some degree, irrespective of whether they are substrates for the transporters. This has implications not just for drug disposition in tissues but also for drug–drug interactions. Notably, the authors mention a lack of data on the expression of these transporter groups in the FGT, despite adequate expression data in other compartments. One study examined P-gp localization by immunohistochemistry staining in the upper genital tract of 14 women and found P-gp expression in the ovaries, fallopian tubes, corpus luteum, ectocervix and endocervix, though the degree of expression was highly variable between patients and tissues.51 Additional publications on transporter expression in the FGT are severely lacking. A recent study examined the expression of uptake (OAT1, OAT3, OATP1B1) and efflux (MDR1, MRP2, and MRP4) transporters in vaginal, cervical, and rectal tissue.52 Gene expression of the efflux transporters was variable between subjects but consistently expressed, whereas uptake transporters were rarely expressed in these tissues. Similar trends were observed in protein levels and are supported by drug disposition data.
The inability to visualize the distribution of ARVs within mucosal tissues hinders the progress of PrEP research. Even for ARVs that are known to permeate well into FGT and colorectal tissue, there are few data evaluating drug exposure in specific areas or cellular subsets vulnerable to HIV infection (ie, mucosa vs. submucosa vs. lymphoid aggregates; mononuclear vs. epithelial cells). Techniques that would allow visualization and quantification of ARVs in tissues would be invaluable not only for prevention but also for treatment and eradication strategies. One such approach is matrix-assisted laser desorption/ionization (MALDI): a mass spectrometry technique that has been used since the 1980s for peptide identification.53 Through the use of multiple laser ionizations, MALDI is able to generate information about relative concentrations of tissue constituents which, when coupled with imaging software, allow for the visualization of target analytes within a tissue. Recently, this technique has been modified to identify small molecules within specific tissue areas and even within individual cells.54,55 MALDI has been used previously to quantify ARVs in plasma and represents a promising approach to understanding drug disposition in tissues.56
Another possible avenue for future research could include the use of a quantitative structure activity relationship (QSAR) model to isolate the chemical moieties and PK parameters (eg, protein binding) that improve or hinder penetration. These models have been successfully used to identify structural characteristics that enhance HIV inhibition, but to date, no validated QSAR model has been developed for ARV penetration into the mucosal compartment.57 This model was used to determine penetration of drugs across the blood–brain barrier and achieved a positive predictive value of 100% and negative predictive value of 83%.58 The authors were also able to identify factors, such as binding affinity to efflux transporters, which affect blood–brain barrier penetration. We recently used a similar approach to develop a QSAR model for drug entry into female genital tissues using a newly validated QSAR model for transporter affinity.59 Our model was modestly predictive and identified MRP4 as a novel contributor to FGT penetration.60 Validation of this model and/or the addition of other models of drug penetration into vaginal/cervical and rectal tissues would greatly inform the drug development process and identify PrEP candidates from an early stage.
Finally, biologic factors can affect both ARV penetration into tissues and infection susceptibility. For example, the nucleotide reverse transcriptase inhibitors require intracellular phosphorylation to their active forms through cellular kinase activity. It has been determined that kinase activity in quiescent or activated cells changes the rate and extent of phosphorylation of ARVs. Specifically, zalcitabine, 3TC, stavudine, and didanosine are preferentially phosphorylated in activated cells.61,62 No noted differences in phosphorylation have been found between activated and quiescent cells for TFV.63 Importantly, these differences in active metabolite concentrations may not correlate with antiviral activity because zalcitabine, 3TC, and didanosine are more active against HIV in quiescent cells, despite lower metabolite concentrations than in active cells.62 It may be that increased concentrations of endogenous nucleotides in activated cells decrease their effectiveness.
Altered mucosal integrity may also result in large interindividual variability in ARV penetration, particularly for topical dosage forms. Compromised mucosal integrity has been associated with increased viral penetration.64 It is not known whether this relationship holds true for topical ARV penetration, but inflammation and physical breaks in skin are known to increase plasma exposure to topical products. Furthermore, although the integrity of the upper genital tract tissues (eg, endometrium) is heavily influenced by the menstrual cycle, hormonal influence on the vaginal and rectal mucosa is less understood. There are numerous studies examining the role of estrogen on HIV susceptibility; however, studies exploring the hormonal influence on drug exposure are lacking.65,66
DRUG PERSISTENCE AND FUNCTIONAL HALF-LIFE
Given that the index infection likely takes place within the mucosa or submucosa of mucosal tissues, the presence of adequate concentrations of ARVs at the time of exposure is critical in PrEP. Also critical is the length of time compounds reside in the tissue. Compounds with long tissue half-lives (or delivery systems with continuous drug exposure) would be favored for both virological and adherence factors.4,9,11 For any ARV used in PrEP, the time spent above target concentration must at least be as long as the length of time that viable virus remains in the mucosal cavity after coital exposure. The life span of the HIV virion in plasma has been reported as 6 hours, whereas HIV-infected CD4+ T cells have a life span of approximately 2 days in plasma.67 The life span of both infected cells and virion in the mucosal cavity remains unknown and demands exploration. One study examined virion persistence after vaginal inoculation of simian immunodeficiency virus in macaques and found that low levels (hundreds to 10,000 copies per microgram tissue) were present 1 day after inoculation.25 If we assume that the life span in the mucosal cavities are identical to those in plasma, then protective ARV concentrations would need to be continually present for up to 3 days after each exposure. Recently, the iPrEX, FemPreP, and VOICE studies have demonstrated that study volunteers have difficulty adhering to a once-daily dosing regimen, which compromises PrEP efficacy.9,11,12 These studies demonstrated that daily prophylaxis against HIV infection (whether oral or topical) will be minimally effective if the functional half-life is too short, or the mucosal tissue penetration too low, to permit any reasonable degree of tissue protection.
TFV and FTC have reported plasma half-lives of 17 and 10 hours, respectively. However, the half-lives of their active intracellular metabolites (TFV-dp and FTC-tp) in peripheral blood mononuclear cells are much longer at approximately 144 and 38 hours, respectively.68,69 In mucosal tissues, we have documented that TFV-dp and FTC-tp have half-lives of 2–6 days.30 We have also noted that the high TFV and TFV-dp exposures achieved in colorectal tissue (×100 higher than vaginal or cervical tissue) after a single dose were advantageous to the iPrEX cohort of men who have sex with men who did not take daily TFV/FTC (Truvada) as instructed but rather intermittently and yet were still protected from HIV infection.9,70
Despite potential advantages in PrEP, a number of concerns are inherent with a long half-life compound: in particular, the development of resistance. Due to an increase in elimination time, there may be extended periods where drug concentrations are subtherapeutic in mucosal tissues. If HIV transmission occurs during this time, prolonged exposure to subtherapeutic drug concentrations has the potential to select for viral resistance.71 This is especially true for long-acting injectables, where subtherapeutic concentrations may persist for weeks rather than hours.41 Obviously, allergic reactions might also be exacerbated with unremitting exposure to an allergen as was observed with penicillin and serum sickness.72
GENERATING EFFECTIVE DRUG TARGET CONCENTRATIONS AND DOSING STRATEGIES
To ensure adequate ARV drug concentrations within mucosal tissue, therapeutic tissue concentration targets must be defined. To date, target ARV tissue concentrations for HIV prevention have not been established, but if determined would represent an important advance in PrEP research. Once the appropriate models for defining these are identified, dosing strategies can be designed to achieve concentrations above this target while preventing long periods of subtherapeutic drug exposure and minimizing the risk of drug resistance.
The variable efficacy of topical and systemic PrEP observed in clinical trials is highly dependent on adherence but is also due to limited mucosal tissue penetration for the ARVs studied thus far. Numerous methods are currently under investigation to identify those drugs and concentrations that successfully prevent HIV infection on exposure to the virus. These include cellular studies, humanized mice and nonhuman primate models, the human mucosal tissue explant model, and retrospective analysis of clinical trial data.73–75 The generation of “threshold” ARV concentrations above which HIV transmission is unlikely would provide a target around which dosing strategies could be generated for clinical studies.
PD measures of efficacy, such as time above minimum inhibitory concentration, have been successfully implemented as targets to guide antibiotic dosing. Similar measures of efficacy need to be developed for HIV chemoprophylaxis. The process is complex, requiring dose fractionation to determine the best efficacy target.76 Unfortunately, establishing target concentrations in mucosal tissues is a complex process. For example, although bacterial infections are extracellular, and the concentration of antimicrobials in the interstitial fluid is pharmacodynamically active (and can be measured with dialysis techniques or in blister fluid), the intracellular nature of HIV requires an understanding of active intracellular concentrations.76,77 Based on the physicochemical and biologic factors listed above, it is therefore more important to understand protein-unbound drug concentrations in tissues or cells rather than plasma. Furthermore, due to differences in rates of tissue distribution, single time point estimates of drug concentration may be inadequate to fully describe these PK–PD relationships, and multiple sampling to quantify area under the concentration-time curve is necessary. With newer technologies such as MALDI imaging, simultaneously exploring the PD of drug distribution with the PD of anti-HIV effect may be possible.
PK modeling and simulation approaches can identify optimal (preferably coitally independent) dosing strategies for clinical trial investigation, which surpass the target mucosal tissue concentrations for a predefined critical length of time.78–80 Indeed, it would be unreasonable to identify a target concentration that was only achievable by dosing multiple times per day because even once daily dosing has been challenging for some clinical study subjects to adhere to. Adherence has been shown to correlate with efficacy in multiple studies and has been thoroughly reviewed by Koenig et al10,81,82 The factors affecting drug adherence are complex, but the frequency and complexity of the dosing regimen in a healthy population is certainly a contributing factor.83 Several novel formulations are currently in development and may be useful to overcome the adherence barrier.84 For example, a long-acting parenteral ARV formulation or a slow-release vaginal ring formulation should increase the probability of achieving consistent target concentrations. It has yet to be determined if these drug delivery modalities will be acceptable to study volunteers and used more consistently than daily dosed products.
FUTURE DIRECTIONS IN PREVENTION PHARMACOLOGY
The necessity of an effective prophylactic regimen is highlighted by the inability of treatment regimens to completely prevent viral shedding in genital and rectal tissues. HIV RNA is easily detectable in the genital tissues and fluids of HIV-infected women and in the seminal fluid and rectal tissue of HIV-infected men and is highly correlated with plasma RNA levels.85–87 Importantly, viral shedding is reduced by ART as much as 2 log units, demonstrating that therapy likely reduces the infectivity of HIV-infected individuals.5,88 Reduced viral shedding can have profound clinical implications. The HPTN 052 study demonstrated that among serodiscordant couples, early initiation of ART in the infected partner was associated with a 96% reduction in HIV transmission compared with deferred initiation.6 The large decrease in transmission observed in this study would not have been possible without decreased viral shedding. Unfortunately, both genital and rectal shedding have been shown to persist even in the setting of undetectable plasma viral RNA.89–91 Although it is unknown whether the viral RNA found in these tissues represents viable and infectious HIV, it is a concerning finding nonetheless. The apparent inability of treatment regimens to eradicate HIV in the genital tract suggests that effective PrEP will require novel dosing strategies or dosage forms to prevent infection at these sites. What remains unclear is whether a disparity exists between effective ARV concentrations for prevention of acquisition versus prevention of transmission. Concentration–response relationships are well characterized for ARVs in plasma but have not been studied at the tissue level. It is possible that differences in immune cell populations between plasma and tissue have an effect on drug efficacy. For instance, higher levels of HIV targets in rectal tissue compared with blood may require higher concentrations of drug at this site to prevent infection.28
The in vitro and preclinical methods developed to understand ARV PKs and efficacy in mucosal tissue compartments have greatly improved our understanding of ARV pharmacology. However, these are not without limitations. Nonhuman primate models of prevention are limited by the numbers available for study and have some clinically relevant pharmacological and virological distinctions. The humanized mouse model can use clinically relevant viruses, but challenges remain in characterizing pharmacological differences with smaller sampling capacity.73 The human tissue explant model can use relevant tissue and viruses, but data on ARV disposition and PK-PD relationships are lacking because nonstandardized methods and approaches are used.74 Target effective ARV concentrations can be generated from all these models, but a lack of robust and consistent data across all models currently limit our ability to determine how they should be used for informing drug development go/no go decisions and clinical trial design. As previously indicated, PK modeling is critical for generating dose–concentration relationships even in early drug development and should be used for PrEP.92–94 Simulations run on a successful PK model will identify which dosing regimen best achieves target concentrations, once identified. This information will streamline trial development and increase the likelihood of success. The use of modeling and simulation for dosing regimen selection and clinical trial design is an important cost-effective technique, particularly in chemoprophylaxis studies whereby clinical dose-finding studies are unattainable due to patient risk and sample size requirements. Models can be generated which take into account what is already known about a drug and factor in various assumptions, such as intra- and interpatient variability, adherence, and dropout rates.95,96 These strategies have been used in the past for faster market approval.97 An additional benefit of modeling is that once generated, a model can be used not only to evaluate the drug for which it was developed but also for other drugs within that class as well.95 This will be extremely beneficial for PrEP, with multiple candidates being available in similar therapeutic drug classes.
Successful HIV prevention strategies have been demonstrated in clinical trials, but implementation in the real world is a challenge. Use of ARV treatment as prevention has already become policy in the setting of discordant couples and may be expected to inform when ART is started and continued and which drugs are selected.98,99 Curing HIV infection will require that ART stop replication in every compartment, a feat that has already proven a challenge. The mixed results of both topical and systemic PrEP trials demand preclinical and early phase strategies to improve the knowledge of efficacy targets and develop maximally effective dosing strategies that will be accepted by study participants and eventually the target market. The mucosal compartment plays an important role in transmission as the site of first exposure to HIV. Therefore, research aimed at understanding drug targets to prevent infection at this location or even distal to this location (eg, regional lymph nodes) is essential for developing successful next generation PrEP strategies. Determining the optimal time that drug should reside in mucosal tissues will also help define dosing strategies. Factors influencing tissue disposition are poorly understood but should be identified so that chemicals and formulations can be optimally designed for this purpose. Validating animal and ex vivo models against clinical outcomes in humans will determine their utility in making go/no go decisions and informing clinical trial design. Finally, PK/PD and clinical trial modeling and simulation have an important role to play in potentially informing the drug development process and increasing the probability of PrEP success in large clinical trials.
1. Van Sighem AI, Gras LA, Reiss P, et al.. Life expectancy of recently diagnosed asymptomatic HIV-infected patients approaches that of uninfected individuals. AIDS. 2010;24:1527–1535.
3. Kashuba ADM, Dyer JR, Kramer LM, et al.. Antiretroviral-drug concentrations in semen: implications for sexual transmission of human immunodeficiency virus type 1. Antimicrob Agents Chemother. 1999;43:1817–1826.
4. Vernazza PL, Gilliam BL, Flepp M, et al.. Effect of antiviral treatment on the shedding of HIV-1 in semen. AIDS. 1997;11:1249–1254.
5. Vernazza PL, Troiani L, Flepp MJ, et al.. Potent antiretroviral treatment of HIV-infection results in suppression of the seminal shedding of HIV. AIDS. 2000;14:117–121.
6. Cohen MS, Chen YQ, McCauley M, et al.. Prevention of HIV-1 infection with early antiretroviral therapy. N Engl J Med. 2011;365:493–505.
7. Connor EM, Sperling RS, Gelber R, et al.. Reduction of maternal-infant transmission of human immunodeficiency virus type 1 with zudovudine treatment. N Engl J Med. 1994;331:1173–1180.
8. Cardo DM, Culver DH, Ciesielski CA. A case-control study of HIV seroconversion in health care workers after percutaneous exposure. N Engl J Med. 1997;337:1485–1490.
9. Grant RM, Lama JR, Anderson PL, et al.. Preexposure chemoprophylaxis for HIV prevention in men who have sex with men. N Engl J Med. 2010;363:2587–2599.
10. Karim QA, Karim SSA, Frohlich JA, et al.. Effectiveness and safety of tenofovir gel, and antiretroviral microbicide, for the prevention of HIV infection in women. Science. 2010;329:1168–1174.
11. Van Damme L, Corneli A, Ahmed K, et al.. Preexposure prophylaxis for HIV infection among African women. N Engl J Med. 2012;367:411–422.
12. Marrazzo J, Ramjje G, Nair G, et al.. Pre-exposure prophylaxis for HIV in women: daily oral tenofovir, oral tenofovir/emtricitabine, or vaginal tenofovir gel in the VOICE study (MTN 003). Paper presented at: XX Conference on Retroviruses and Opportunistic Infections; March 4, 2013; Atlanta, GA.
13. Whelton A, Blanco L, Carter G. Therapeutic implications of doxycycline and cephalothin concentrations in the female genital tract. Obstet Gynecol. 1980;55:28–32.
14. Gall S, Hemsell DL, McGregor J, et al.. Tissue penetration of meropenem in patients undergoing gynecologic surgery. Clin Infect Dis. 1997;24(suppl 2):S178–S180.
15. Martens MG, Maccato M, Van Hook C, et al.. Penetration of trovafloxacin into gynecologic tissues. Am J Surg. 1998;176(suppl):18S–22S.
16. Iliopoulou A, Thin RN, Turner P. Fluorimetric and microbiological assays of erythromycin concentrations in plasma and vaginal washings. Br J Vener Dis. 1981;57:263–267.
17. Heykants JJ, Woestenborghs RJ, Bisschop MP, et al.. Distribution of oral ketoconazole to vaginal tissue. Eur J Clin Pharmacol. 1982;23:331–333.
18. Larosa E, Cauwenbergh G, Cilli P, et al.. Itraconazole pharmacokinetics in the female genital tract: plasma and tissue levels in patients undergoing hysterectomy after a single dose of 200 mg itraconazole. Eur J Obstet Gynecol Reprod Biol. 1986;23:85–89.
19. Dumond JB, Yeh RF, Patterson KB, et al.. Antiretroviral drug exposure in the female genital tract: implications for oral pre- and post-exposure prophylaxis. AIDS. 2007;21:1899–1907.
20. Dumond JB, Patterson KB, Pecha AL, et al.. Maraviroc concentrations in the cervicovaginal fluid and vaginal tissue of HIV-negative women. J Acquir Immune Defic Syndr. 2009;51:546–553.
21. Min SS, Corbett AH, Rezk N, et al.. Protease inhibitor and nonnucleoside reverse transcriptase inhibitor concentrations in the genital tract of HIV-1-infected women. J Acquir Immune Defic Syndr. 2004;37:1577–1580.
22. Karim SSA, Kashuba ADM, Werner L, et al.. Drug concentrations after topical and oral antiretroviral pre-exposure prophylaxis: implications for HIV prevention in women. Lancet. 2011;378:279–281.
23. Hladik F, Hope TJ. HIV infection of the genital mucosa in women. Curr HIV/AIDS Rep. 2009;6:20–28.
24. Haase AT. Early events in sexual transmission of HIV and SIV and opportunities for interventions. Annu Rev Med. 2011;62:127–139.
25. Miller CJ, Li Q, Abel K, et al.. Propagation and dissemination of infection after vaginal transmission of simian immunodeficiency virus. J Virol. 2005;79:9217–9227.
26. Hu J, Gardner MB, Miller CJ. Simian immunodeficiency virus rapidly penetrates the cervicovaginal mucosa after intravaginal inoculation and infects intraepithelial dendritic cells. J Virol. 2000;74:6087–6095.
27. Padian NS, Van Der SA, Ramjee G, et al.. Diaphragm and lubricant gel for prevention of HIV acquisition in southern African women: a randomised controlled trial. Lancet. 2008;370:251–261.
28. Tebit DM, Ndembi N, Weinberg A, et al.. Mucosal transmission of human immunodeficiency virus. Curr HIV Res. 2012;10:3–8.
29. Lane T, Pettifor A, Pascoe S, et al.. Heterosexual anal intercourse increases risk of HIV infection among young South African men. AIDS. 2006;20:119–132.
30. Patterson KB, Prince HA, Kraft E, et al.. Penetration of tenofovir and emtricitabine in mucosal tissues: implications for prevention of HIV-1 transmission. Sci Transl Med. 2012;3:112re4.
31. Kwara A, Delong A, Rezk N, et al.. Antiretroviral drug concentrations and HIV RNA in the genital tract of HIV-infected women receiving long-term highly active antiretroviral therapy. Clin Infect Dis. 2008;46:719–725.
32. Else LJ, Taylor S, Back DJ, et al.. Pharmacokinetics of antiretroviral drugs in anatomical sanctuary sites: the male and female genital tract. Antivir Ther. 2011;16:1149–1167.
33. Brown KC, Patterson KB, Jennings SH, et al.. Single- and multiple-dose pharmacokinetics of darunavir plus ritonavir and etravirine in semen and rectal tissue of HIV-negative men. J Acquir Immune Defic Syndr. 2012;61:138–144.
34. Patterson K, Jennings S, Falcon R, et al.. Darunavir, ritonavir, and etravirine pharmacokinetics in the cervicovaginal fluid and blood plasma of HIV-infected women. Antimicrob Agents Chemother. 2011;55:1120–1122.
35. Jones A, Talameh J, Patterson K. First-dose and steady-state pharmacokinetics of raltegravir in the genital tract of HIV negative women. Paper presented at: X International Workshop on Clinical Pharmacology of HIV Therapy; April 16, 2009; Amsterdam, The Netherlands.
36. Yeh RF, Rezk NL, Kashuba ADM, et al.. Genital tract, cord blood, and amniotic fluid exposures of seven antiretroviral drugs during and after pregnancy in human immunodeficiency virus type 1-infected women. Antimicrob Agents Chemother. 2009;53:2367–2374.
37. Launay O, Tod M, Louchahi K, et al.. Differential diffusions of indinavir and lopinavir in genital secretions of human immunodeficiency virus-infected women. Antimicrob Agents Chemother. 2004;48:632–634.
38. Clavel C, Mandelbrot L, Marcelin A. Raltegravir concentrations in the cervicovaginal compartment exceed the median inhibitory concentration in HIV-1-infected women treated with a raltegravir-containing regimen: DIVA 01 Study. Paper presented at: XVII Conference on Retroviruses and Opportunistic Infections; February 18, 2010; San Francisco, CA.
39. Greener B, Adams J, Patterson K. Single and multiple dose dolutegravir pharmacokinetics in the genital tract and colorectum of HIV-negative men and women. Paper presented at: XX Conference on Retroviruses and Opportunistic Infections; March 5, 2013; Atlanta, GA.
40. Brown KC, Patterson KB, Malone S, et al.. Single and multiple dose pharmacokinetics of maraviroc in saliva, semen, and rectal tissue of healthy HIV-negative men. J Infect Dis. 2011;203:1484–1490.
41. Else LJ, Jackson A, Tija J. Pharmacokinetics of long-acting rilpivirine in plasma, genital tract, and rectum of HIV-negative females and males administered a single 600mg dose. Paper presented at: XIII International Workshop on Clinical Pharmacology of HIV Therapy; April 17, 2012; Barcelona, Spain.
42. Andrews C, Gettie A, Russell-Lodrigue K, et al.. Long-acting parenteral formulation of GSK1265744 protects macaques against repeated intrarectal challenges with SHIV. Paper presented at: XX Conference on Retroviruses and Opportunistic Infections; 2013; Atlanta, GA.
43. Nuttall J, Kashuba A, Wang R, et al.. Pharmacokinetics of tenofovir following intravaginal and intrarectal administration of tenofovir gel to rhesus macaques. Antimicrob Agents Chemother.. 2012;56:103–109.
44. Johnson TJ, Clark MR, Albright TH, et al.. A 90-day tenofovir reservoir intravaginal ring for mucosal HIV prophylaxis. Antimicrob Agents Chemother. 2012;56:6272–6283.
45. Nel A, Smythe S, Youg K, et al.. Safety and pharmacokinetics of dapivirine delivery from matrix and reservoir intravaginal rings to HIV-negative women. J Acquir Immune Defic Syndr. 2009;51:416–423.
46. Lin JH. Tissue distribution and pharmacodynamics: a complicated relationship. Curr Drug Metab. 2006;7:39–65.
47. Theuretzbacher U. Tissue penetration of antibacterial agents: how should this be incorporated into pharmacodynamic analyses? Curr Opin Pharmacol. 2007;7:498–504.
48. Henry K, Chinnock BJ, Quinn RP, et al.. Concurrent zidovudine levels in semen and serum determined by radioimmunoassay in patients with AIDS or AIDS-related complex. JAMA. 1988;259:3023–3026.
49. Cao YJ, Hendrix CW. Male genital tract pharmacology: developments in quantitative methods to better understand a complex peripheral compartment. Clin Pharmacol Ther. 2008;83:401–412.
50. Kis O, Robillard K, Chan GNY, et al.. The complexities of antiretroviral drug-drug interactions: role of ABC and SLC transporters. Trends Pharmacol Sci. 2010;31:22–35.
51. Finstad CL, Saigo PE, Rubin SC, et al.. Immunohistochemical localization of P-glycoprotein in adult human ovary and female genital tract of patients with benign gynecological conditions. J Histochem Cytochem. 1990;38:1677–1681.
52. Nicol M, Fedoriw Y, Mathews M, et al.. Gene and protein expression of drug transporters in vaginal, cervical, and rectal tissues: implications for drug disposition in HIV prevention. Paper presented at: XX Conference on Retroviruses and Opportunistic Infections; March 5, 2013; Atlanta, GA.
53. Zhou M, Veenstra T. Mass spectrometry: m/z 1983–2008. Biotechniques. 2008;44:667–668–670, .
54. Reyzer ML, Caprioli RM. MALDI-MS-based imaging of small molecules and proteins in tissues. Curr Opin Chem Biol. 2007;11:29–35.
55. Zavalin A, Todd EM, Rawhouser PD, et al.. Direct imaging of single cells and tissue at sub-cellular spatial resolution using transmission geometry MALDI MS. J Mass Spectrom. 2012;47:1473–1481.
56. Meesters RJW, Van Kampen JJ, Scheuer RD, et al.. Determination of the antiretroviral drug tenofovir in plasma from HIV-infected adults by ultrafast isotope dilution MALDI-triple quadrupole tandem mass spectrometry. J Mass Spectrom. 2011;46:282–289.
57. Srivastava HK, Bohari MH, Sastry GN. Modeling anti-HIV compounds: the role of analogue-based approaches. Curr Comput Aided Drug Des. 2012;8:224–248.
58. Zhang L, Zhu H, Oprea TI, et al.. QSAR modeling of the blood-brain barrier permeability for diverse organic compounds. Pharm Res. 2008;25:1902–1914.
59. Sedykh A, Fourches D, Duan J, et al.. Human intestinal transporter database: QSAR modeling and virtual profiling of drug uptake, efflux and interactions. Pharm Res. 2013;30:996–1007.
60. Thompson C, Sedykh A, Nicol M, et al.. Prediction of antiretroviral drug penetration into the female genital tract using a novel QSAR model. Paper presented at: XIV International Workshop on Clinical Pharmacology of HIV; April 23, 2013; Amsterdam, The Netherlands.
61. Perno CF, Cooney D a, Gao WY, et al.. Effects of bone marrow stimulatory cytokines on human immunodeficiency virus replication and the antiviral activity of dideoxynucleosides in cultures of monocyte/macrophages. Blood. 1992;80:995–1003.
62. Gao WY, Agbaria R, Driscoll JS, et al.. Divergent anti-human immunodeficiency virus activity and anabolic phosphorylation of 2′,3′-dideoxynucleoside analogs in resting and activated human cells. J Biol Chem. 1994;269:12633–12638.
63. Robbins B, Wilcox C, Fridland A. Metabolism of tenofovir and didanosine in quiescent or stimulated human peripheral blood mononuclear cells. Pharmacotherapy. 2003;23:695–701.
64. Mayer KH, Venkatesh KK. Interactions of HIV, other sexually transmitted diseases, and genital tract inflammation facilitating local pathogen transmission and acquistion. Am J Reprod Immunol. 2012;65:308–316.
65. Brabin L. Interactions of the female hormonal environment, susceptibility to viral infections, and disease progression. AIDS Patient Care STDs. 2002;16:211–221.
66. Mingjia L, Short R. How oestrogen or progesterone might change a woman’s susceptibility to HIV-1 infection. Aust N Z J Obstet Gynaecol. 2002;42:472–475.
67. Perelson AS, Neumann AU, Markowitz M, et al.. HIV-1 dynamics in vivo: virion clearance rate, infected cell life-span, and viral generation time. Science. 1996;271:1582–1586.
68. Hawkins T, Veikley W, St. Claire RL, et al.. Intracellular pharmacokinetics of tenofovir diphosphate, in patients receiving triple-nucleoside regimens. J Acquir Immune Defic Syndr. 2005;39:406–411.
69. Adams JL, Sykes C, Menezes P, et al.. Tenofovir diphosphate and emtricitabine triphosphate concentrations in blood cells compared with isolated peripheral blood mononuclear cells: a new measure of antiretroviral adherence? J Acquir Immune Defic Syndr. 2013 [Epub ahead of print].
70. Kashuba ADM, Patterson KB, Dumond JB, et al.. Pre-exposure prophylaxis for HIV prevention: how to predict success. Lancet. 2012;379:2409–2411.
71. González de Requena D, Gallego O, De Mendoza C, et al.. Indinavir plasma concentrations and resistance mutations in patients experiencing early virological failure. AIDS Res Hum Retroviruses. 2003;19:457–459.
72. Clark BM, Kotti GH, Shah AD, et al.. Severe serum sickness reaction to oral and intramuscular penicillin. Pharmacotherapy. 2006;26:705–708..
73. Akkina R. New generation humanized mice for virus research: comparative aspects and future prospects. Virology. 2013;435:14–28.
74. Dezzutti CS, Hladik F. Use of human mucosal tissue to study HIV-1 pathogenesis and evaluate HIV-1 prevention modalities. Curr HIV/AIDS Rep. 2012;74:12–20.
75. Anderson PL, Glidden DV, Liu A, et al.. Emtricitabine-tenofovir concentrations and pre-exposure prophylaxis efficacy in men who have sex with men. Sci Transl Med. 2012;4:151ra125.
76. Craig WA. Pharmacokinetic/pharmacodynamic parameters: rationale for antibacterial dosing of mice and men. Clin Infect Dis. 1998;26:1–10.
77. Andes D, Anon J, Jacobs M, et al.. Application of pharmacokinetics and pharmacodynamics to antimicrobial therapy of community-acquired respiratory tract infections. Clin Lab Med. 2004;24:477–502.
78. Barrett JS. Facilitating compound progression of antiretroviral agents via modeling and simulation. J Neuroimmune Pharmacol. 2007;2:58–71.
79. Guidi M, Arab-Alameddine M, Rotger M, et al.. Dosage optimization of treatments using population pharmacokinetic modeling and simulation. CHIMIA. 2012;66:291–295.
80. Barrett JS, Labbé L, Pfister M. Application and impact of population pharmacokinetics in the assessment of antiretroviral pharmacotherapy. Clin Pharmacokinet. 2005;44:591–625.
81. Tangmunkongvorakul A, Chariyalertsak S, Amico KR, et al.. Facilitators and barriers to medication adherence in an HIV prevention study among men who have sex with men in the iPrEx study in Chiang Mai, Thailand. AIDS Care. 2012 [Epub ahead of print].
82. Koenig LJ, Lyles C, Smith DK. Adherence to antiretroviral medications for HIV pre-exposure prophylaxis: lessons learned from trials and treatment studies. Am J Prev Med. 2013;44(suppl 2):S91–S98.
83. Muchomba FM, Gearing RE, Simoni JM, et al.. State of the science of adherence in pre-exposure prophylaxis and microbicide trials. J Acquir Immune Defic Syndr. 2012;61:490–498.
84. Abraham BK, Gulick R. Next-generation oral preexposure prophylaxis: beyond tenofovir. Curr Opin HIV AIDS. 2012;7:600–606.
85. Mostad SB, Kreiss JK. Shedding of HIV-1 in the genital tract. AIDS. 1996;10:1305–1315.
86. Goulston C, McFarland W, Katzenstein D. Human immunodeficiency virus type 1 RNA shedding in the female genital tract. J Infect Dis. 1998;177:1100–1103.
87. Kiviat NB, Critchlow CW, Hawes SE, et al.. Determinants of human immunodeficiency virus DNA and RNA shedding in the anal-rectal canal of homosexual men. J Infect Dis. 1998;177:571–578.
88. Cu-Uvin S, Caliendo a M, Reinert S, et al.. Effect of highly active antiretroviral therapy on cervicovaginal HIV-1 RNA. AIDS. 2000;14:415–421.
89. Zuckerman RA, Whittington WLH, Celum CL, et al.. Higher concentration of HIV RNA in rectal mucosa secretions than in blood and seminal plasma, among men who have sex with men, independent of antiretroviral therapy. J Infect Dis. 2004;190:156–161.
90. Cu-Uvin S, DeLong AK, Venkatesh KK, et al.. Genital tract HIV-1 RNA shedding among women with below detectable plasma viral load. AIDS. 2010;24:2489–2497.
91. Neely M, Benning L, Xu J, et al.. Cervical shedding of HIV-1 among women with low levels of viremia while receiving highly active antiretroviral therapy. J Acquir Immune Defic Syndr. 2011;44:38–42.
92. Chen B, Dong JQ, Pan WJ, et al.. Pharmacokinetics/pharmacodynamics model-supported early drug development. Curr Pharm Biotechnol. 2012;13:1360–1375.
93. Peck CC. Quantitative clinical pharmacology is transforming drug regulation. J Pharmacokinet Pharmacodyn. 2010;37:617–628.
94. Gibbs JP. Prediction of exposure-response relationships to support first-in-human study design. AAPS J. 2010;12:750–758.
95. Rooney KF, Snoeck E, Watson PH. Modeling and simulation in clinical drug development. Drug Discov Today. 2001;6:802–806.
96. De Ridder F. Predicting the outcome of phase III trials using phase II data: a case study of clinical trial simulation in late stage drug development. Basic Clin Pharmacol Toxicol. 2005;96:235–241.
97. Zhang L, Sinha V, Forgue ST, et al.. Model-based drug development: the road to quantitative pharmacology. J Pharmacokinet Pharmacodyn. 2006;33:369–393.
© 2013 Lippincott Williams & Wilkins, Inc.