Cytochrome P450-mediated drug interactions affecting lidocaine

Lidocaine is a widely used local anaesthetic agent that also has anti-arrhythmic effects. It is classified as a type Ib anti-arrhythmic agent and is used to treat ventricular tachycardia or ventricular fibrillation. Lidocaine is eliminated mainly by metabolism, and less than 5% is excreted unchanged in urine. Lidocaine is a drug with a medium to high extraction ratio, and its bioavailability is about 30%. Based on in vitro studies, the earlier understanding was that CYP3A4 is the major cytochrome P450 (CYP) enzyme involved in the metabolism of lidocaine. When this work was initiated, there was little human data on the effect of inhibitors of CYP enzymes on the pharmacokinetics of lidocaine. Because lidocaine has a low therapeutic index, medications that significantly inhibit lidocaine clearance (CL) could increase the risk of toxicity. These studies investigated the effects of some clinically important CYP1A2 and CYP3A4 inhibitors on the pharmacokinetics of lidocaine administered by different routes. All of the studies were randomized, double-blind, placebo-controlled cross-over studies in two or three phases in healthy volunteers. Pretreatment with clinically relevant doses of CYP3A4 inhibitors erythromycin and itraconazole or CYP1A2 inhibitors fluvoxamine and ciprofloxacin was followed by a single dose of lidocaine. Blood samples were collected to determine the pharmacokinetic parameters of lidocaine and its main metabolites monoethylglycinexylidide (MEGX) and 3-hydroxylidocaine (3-OH-lidocaine). Itraconazole and erythromycin had virtually no effect on the pharmacokinetics of intravenous lidocaine, but erythromycin slightly prolonged the elimination half-life (t½) of lidocaine (Study I). When lidocaine was taken orally, both erythromycin and itraconazole increased the peak concentration (Cmax) and the area under the concentration-time curve (AUC) of lidocaine by 40-70% (Study II). Compared with placebo and itraconazole, erythromycin increased the Cmax and the AUC of MEGX by 40-70% when lidocaine was given intravenously or orally (Studies I and II). The pharmacokinetics of inhaled lidocaine was unaffected by concomitant administration of itraconazole (Study III). Fluvoxamine reduced the CL of intravenous lidocaine by 41% and prolonged the t½ of lidocaine by 35%. The mean AUC of lidocaine increased 1.7-fold (Study IV). After oral administration of lidocaine, the mean AUC of lidocaine in-creased 3-fold and the Cmax 2.2-fold by fluvoxamine (Study V). During the pretreatment with fluvoxamine combined with erythromycin, the CL of intravenous lidocaine was 53% smaller than during placebo and 21% smaller than during fluvoxamine alone. The t½ of lidocaine was significantly longer during the combination phase than during the placebo or fluvoxamine phase. The mean AUC of intravenous lidocaine increased 2.3-fold and the Cmax 1.4-fold (Study IV). After oral administration of lidocaine, the mean AUC of lidocaine increased 3.6-fold and the Cmax 2.5-fold by concomitant fluvoxamine and erythromycin. The t½ of oral lidocaine was significantly longer during the combination phase than during the placebo (Study V). When lidocaine was given intravenously, the combination of fluvoxamine and erythromycin prolonged the t½ of MEGX by 59% (Study IV). Compared with placebo, ciprofloxacin increased the mean Cmax and AUC of intravenous lidocaine by 12% and 26%, respectively. The mean plasma CL of lidocaine was reduced by 22% and its t½ prolonged by 7% (Study VI). These studies clarify the principal role of CYP1A2 and suggest only a modest role of CYP3A4 in the elimination of lidocaine in vivo. The inhibition of CYP1A2 by fluvoxamine considerably reduces the elimination of lidocaine. Concomitant use of fluvoxamine and the CYP3A4 inhibitor erythromycin further increases lidocaine concentrations. The clinical implication of this work is that clinicians should be aware of the potentially increased toxicity of lidocaine when used together with inhibitors of CYP1A2 and particularly with the combination of drugs inhibiting both CYP1A2 and CYP3A4 enzymes.

Studies on CYP2C8-mediated drug interactions

Useiden lääkkeiden yhtäaikainen käyttö on nykyään hyvin yleistä, mikä lisää lääkeaineiden haitallisten yhteisvaikutusten riskiä. Lääkeaineiden poistumisessa elimistöstä ovat tärkeässä osassa niitä hajottavat (metaboloivat) maksan sytokromi P450 (CYP) entsyymit. Vasta aivan viime vuosina on havaittu, että CYP2C8-entsyymillä voi olla tärkeä merkitys mm. lääkeaineyhteisvaikutuksissa. Eräät lääkeaineet voivat estää (inhiboida) CYP2C8-entsyymin kautta tapahtuvaa metaboliaa. Tässä työssä selvitettiin CYP2C8-entsyymiä estävien lääkkeiden vaikutusta sellaisten lääkeaineiden pitoisuuksiin, joiden aikaisemman tiedon perusteella arveltiin metaboloituvan CYP2C8-välitteisesti. Näiden lääkeaineiden metaboliaa tutkittiin myös koeputkiolosuhteissa (in vitro -menetelmillä). Lisäksi CYP2C8-entsyymiä estävän lipidilääke gemfibrotsiilin yhteisvaikutusmekanismia tutkittiin selvittämällä interaktion säilymistä koehenkilöillä gemfibrotsiilin annostelun lopettamisen jälkeen. Yhteisvaikutuksia tutkittiin terveillä vapaaehtoisilla koehenkilöillä käyttäen vaihtovuoroista koeasetelmaa. Koehenkilöille annettiin CYP2C8-entsyymiä estävää lääkitystä muutaman päivän ajan ja tämän jälkeen kerta-annos tutkimuslääkettä. Koehenkilöiltä otettiin useita verinäytteitä, joista määritettiin lääkepitoisuudet nestekromatografisilla tai massaspektrometrisillä menetelmillä. Gemfibrotsiili nosti ripulilääke loperamidin pitoisuudet keskimäärin kaksinkertaiseksi. Gemfibrotsiili lisäsi, mutta vain hieman, kipulääke ibuprofeenin pitoisuuksia, eikä sillä ollut mitään vaikutusta unilääke tsopiklonin pitoisuuksiin toisin kuin aiemman kirjallisuuden perusteella oli odotettavissa. Toinen CYP2C8-estäjä, mikrobilääke trimetopriimi, nosti diabeteslääke pioglitatsonin pitoisuuksia keskimäärin noin 40 %. Gemfibrotsiili nosti diabeteslääke repaglinidin pitoisuudet 7-kertaiseksi ja tämä yhteisvaikutus säilyi lähes yhtä voimakkaana vielä 12 tunnin päähän viimeisestä gemfibrotsiiliannoksesta. Tehdyt havainnot ovat käytännön lääkehoidon kannalta merkittäviä ja ne selvittävät CYP2C8-entsyymin merkitystä useiden lääkkeiden metaboliassa. Gemfibrotsiilin tai muiden CYP2C8-entsyymiä estävien lääkkeiden yhteiskäyttö loperamidin kanssa voi lisätä loperamidin tehoa tai haittavaikutuksia. Toisaalta CYP2C8-entsyymin osuus tsopiklonin ja ibuprofeenin metaboliassa näyttää olevan pieni. Trimetopriimi nosti kohtalaisesti pioglitatsonin pitoisuuksia, ja kyseisten lääkkeiden yhteiskäyttö voi lisätä pioglitatsonin annosriippuvaisia haittavaikutuksia. Gemfibrotsiili-repaglinidi-yhteisvaikutuksen päämekanismi in vivo näyttää olevan CYP2C8-entsyymin palautumaton esto. Tämän vuoksi gemfibrotsiilin estovaikutus ja yhteisvaikutusriski säilyvät pitkään gemfibrotsiilin annostelun lopettamisen jälkeen, mikä tulee ottaa huomioon käytettäessä sitä CYP2C8-välitteisesti metaboloituvien lääkkeiden kanssa.

Computational systems approach for drug target discovery

Importance of the field: The shift in focus from ligand based design approaches to target based discovery over the last two to three decades has been a major milestone in drug discovery research. Currently, it is witnessing another major paradigm shift by leaning towards the holistic systems based approaches rather the reductionist single molecule based methods. The effect of this new trend is likely to be felt strongly in terms of new strategies for therapeutic intervention, new targets individually and in combinations, and design of specific and safer drugs. Computational modeling and simulation form important constituents of new-age biology because they are essential to comprehend the large-scale data generated by high-throughput experiments and to generate hypotheses, which are typically iterated with experimental validation. Areas covered in this review: This review focuses on the repertoire of systems-level computational approaches currently available for target identification. The review starts with a discussion on levels of abstraction of biological systems and describes different modeling methodologies that are available for this purpose. The review then focuses on how such modeling and simulations can be applied for drug target discovery. Finally, it discusses methods for studying other important issues such as understanding targetability, identifying target combinations and predicting drug resistance, and considering them during the target identification stage itself. What the reader will gain: The reader will get an account of the various approaches for target discovery and the need for systems approaches, followed by an overview of the different modeling and simulation approaches that have been developed. An idea of the promise and limitations of the various approaches and perspectives for future development will also be obtained. Take home message: Systems thinking has now come of age enabling a `bird's eye view' of the biological systems under study, at the same time allowing us to `zoom in', where necessary, for a detailed description of individual components. A number of different methods available for computational modeling and simulation of biological systems can be used effectively for drug target discovery.

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: A simulation study

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

Prostate cancer organoids: A potential new tool for testing drug sensitivity

Recent technical advances have enabled for the first time, reliable in vitro culture of prostate cancer samples as prostate cancer organoids. This breakthrough provides the significant possibility of high throughput drug screening covering the spectrum of prostate cancer phenotypes seen clinically. These advances will enable precision medicine to become a reality, allowing patient samples to be screened for effective therapeutics ex vivo, with tailoring of treatments specific to that individual. This will hopefully lead to enhanced clinical outcomes, avoid morbidity due to ineffective therapies and improve the quality of life in men with advanced prostate cancer.

Common and rare variants of the renin-angiotensin system and their relation to antihypertensive drug responses

Most of the diseases affecting public health, like hypertension, are multifactorial by etiology. Hypertension is influenced by genetic, life style and environmental factors. Estimation of the influence of genes to the risk of essential hypertension varies from 30 to 50%. It is plausible that in most of the cases susceptibility to hypertension is determined by the action of more than one gene. Although the exact molecular mechanism underlying essential hypertension remains obscure, several monogenic forms of hypertension have been identified. Since common genetic variations may predict, not only to susceptibility to hypertension, but also response to antihypertensive drug therapy, pharmacogenetic approaches may provide useful markers in finding relations between candidate genes and phenotypes of hypertension. The aim of this study was to identify genetic mutations and polymorphisms contributing to human hypertension, and examine their relationships to intermediate phenotypes of hypertension, such as blood pressure (BP) responses to antihypertensive drugs or biochemical laboratory values. Two groups of patients were investigated in the present study. The first group was collected from the database of patients investigated in the Hypertension Outpatient Ward, Helsinki University Central Hospital, and consisted of 399 subjects considered to have essential hypertension. Frequncies of the mutant or variant alleles were compared with those in two reference groups, healthy blood donors (n = 301) and normotensive males (n = 175). The second group of subjects with hypertension was collected prospectively. The study subjects (n=313) underwent a protocol lasting eight months, including four one-month drug treatment periods with antihypertensive medications (thiazide diuretic, β-blocker, calcium channel antagonist, and an angiotensin II receptor antagonist). BP responses and laboratory values were related to polymorphims of several candidate genes of the renin-angiotensin system (RAS). In addition, two patients with typical features of Liddle’s syndrome were screened for mutations in kidney epithelial sodium channel (ENaC) subunits. Two novel mutations causing Liddle’s syndrome were identified. The first mutation identified located in the beta-subunit of ENaC and the second mutation found located in the gamma-subunit, constituting the first identified Liddle mutation locating in the extracellular domain. This mutation showed 2-fold increase in channel activity in vitro. Three gene variants, of which two are novel, were identified in ENaC subunits. The prevalence of the variants was three times higher in hypertensive patients (9%) than in reference groups (3%). The variant carriers had increased daily urinary potassium excretion rate in relation to their renin levels compared with controls suggesting increased ENaC activity, although in vitro they did not show increased channel activity. Of the common polymorphisms of the RAS studied, angiotensin II receptor type I (AGTR1) 1166 A/C polymorphism was associated with modest changes in RAS activity. Thus, patients homozygous for the C allele tended to have increased aldosterone and decreased renin levels. In vitro functional studies using transfected HEK293 cells provided additional evidence that the AGTR1 1166 C allele may be associated with increased expression of the AGTR1. Common polymorphisms of the alpha-adducin and the RAS genes did not significantly predict BP responses to one-month monotherapies with hydroclorothiazide, bisoprolol, amlodipin, or losartan. In conclusion, two novel mutations of ENaC subunits causing Liddle’s syndrome were identified. In addition, three common ENaC polymorphisms were shown to be associated with occurrence of essential hypertension, but their exact functional and clinical consequences remain to be explored. The AGTR1 1166 C allele may modify the endocrine phenotype of hypertensive patients, when present in homozygous form. Certain widely studied polymorphisms of the ACE, angiotensinogen, AGTR1 and alpha-adducin genes did not significantly affect responses to a thiazide, β-blocker, calcium channel antagonist, and angiotensin II receptor antagonist.

Prospecting for alternate sources of shikimic acid, a precursor of Tamiflu, a bird-flu drug

Shikimic acid, more commonly known by its anionic form, shikimate, is an important intermediate compound of the ‘shikimate pathway’ in plants and microorganisms1. It is the principal precursor for the synthesis of aromatic amino acids, phenylalanine, tryptophan and tyrosine and other compounds such as alkaloids, phenolics and phenyl propanoids2. It is used extensively as a chiral building block for the synthesis of a number of compounds in both pharmaceutical and cosmetic industries3. In the recent past, the focus on shikimic acid has increased since it is the key precursor for the synthesis of Tamiflu, the only drug against avian flu caused by the H5N1 virus4,5. Shikimic acid is converted to a diethyl ketal intermediate, which is then reduced in two steps to an epoxide that is finally transformed to Tamiflu6.

Anti-TNF treatment in juvenile idiopathic arthritis and associated uveitis : Clinical perspectives on growth, uveitis, and drug survival

Juvenile idiopathic arthritis (JIA) is a heterogeneous group of childhood chronic arthritides, associated with chronic uveitis in 20% of cases. For JIA patients responding inadequately to conventional disease-modifying anti-rheumatic drugs (DMARDs), biologic therapies, anti-tumor necrosis factor (anti-TNF) agents are available. In this retrospective multicenter study, 258 JIA-patients refractory to DMARDs and receiving biologic agents during 1999-2007 were included. Prior to initiation of anti-TNFs, growth velocity of 71 patients was delayed in 75% and normal in 25%. Those with delayed growth demonstrated a significant increase in growth velocity after initiation of anti-TNFs. Increase in growth rate was unrelated to pubertal growth spurt. No change was observed in skeletal maturation before and after anti-TNFs. The strongest predictor of change in growth velocity was growth rate prior to anti-TNFs. Change in inflammatory activity remained a significant predictor even after decrease in glucocorticoids was taken into account. In JIA-associated uveitis, impact of two first-line biologic agents, etanercept and infliximab, and second-line or third-line anti-TNF agent, adalimumab, was evaluated. In 108 refractory JIA patients receiving etanercept or infliximab, uveitis occurred in 45 (42%). Uveitis improved in 14 (31%), no change was observed in 14 (31%), and in 17 (38%) uveitis worsened. Uveitis improved more frequently (p=0.047) and frequency of annual uveitis flares was lower (p=0.015) in those on infliximab than in those on etanercept. In 20 patients taking adalimumab, 19 (95%) had previously failed etanercept and/or infliximab. In 7 patients (35%) uveitis improved, in one (5%) worsened, and in 12 (60%) no change occurred. Those with improved uveitis were younger and had shorter disease duration. Serious adverse events (AEs) or side-effects were not observed. Adalimumab was effective also in arthritis. Long-term drug survival (i.e. continuation rate on drug) with etanercept (n=105) vs. infliximab (n=104) was at 24 months 68% vs. 68%, and at 48 months 61% vs. 48% (p=0.194 in log-rank analysis). First-line anti-TNF agent was discontinued either due to inefficacy (etanercept 28% vs. infliximab 20%, p=0.445), AEs (7% vs. 22%, p=0.002), or inactive disease (10% vs. 16%, p=0.068). Females, patients with systemic JIA (sJIA), and those taking infliximab as the first therapy were at higher risk for treatment discontinuation. One-third switched to the second anti-TNF agent, which was discontinued less often than the first. In conclusion, in refractory JIA anti-TNFs induced enhanced growth velocity. Four-year treatment survival was comparable between etanercept and infliximab, and switching from first-line to second-line agent a reasonable therapeutic option. During anti-TNF treatment, one-third with JIA-associated anterior uveitis improved.