Publications

Export 183 results:
Sort by: [ Author  (Asc)] Title Type Year
A B C D E F G H I J K L M N O P Q R [S] T U V W X Y Z   [Show ALL]
S
SB, A, Ugboko VI.  2013.  Unusual foreign bodies in the orofacial soft tissue spaces: A report of three cases.. Nig J Clin Pract. 16(3):381-385.
Schnittger, S, Bacher U, Zander AR, Klyuchnikov E, Haferlach T, Kröger N, Oyekunle A.  2011.  Molecular Diagnostics, Targeted Therapy, and the Indication for Allogeneic Stem Cell Transplantation in Acute Lymphoblastic Leukemia. Advances in Hematology. 2011 AbstractWebsite
n/a
Sergi, C, Serra, N, Colomba C, Ayanlade A, Di Carlo P.  2019.  Tuberculosis evolution and climate change: How much work is ahead? Acta Tropica. 190(2):157-158,Elsevier.Website
Seun-Fadipe, CT, Akinsulore AA, Oginni OA.  2019.  Workplace violence and risk for psychiatric morbidity among health workers in a tertiary health care setting in Nigeria: prevalence and correlates. Psychiatry research. 272:730–736.: Elsevier Abstract
n/a
Shacklett, BL, Derdeyn CA, Folayan MO, Landovitz RJ, Anthony C, Behrens A-J, Hope TJ, Landais E, Leal L, Marrazzo JM, Morris L, Mugo N, Ngure K, Noseda V, Ranasinghe S, Tully DC, Voronin Y, Warren M, Wibmer CK, Xie IY, Scarlatti G, Thyagarajan B.  2017.  HIVR4P 2016, partnering for prevention: conference summary and highlights. . AIDS Research and Human Retroviruses Journal . :.doi:10.1089/AID.2017.0125.
Shakur-Still, H, Roberts I, Fawole B, Chaudhri R, El-Sheikh M, Akintan A, Qureshi Z, Kidanto H, Vwalika B, Abdulkadir A, Etuk S, Noor S, Asonganyi Defang E, Alfirevic Z, Beaumont D, Ronsmans C, Arulkumaran S, Grant A, Afsana K, Faye G.  2017.  Effect of early tranexamic acid administration on mortality, hysterectomy, and other morbidities in women with post-partum haemorrhage (WOMAN): An international, randomised, double-blind, placebo-controlled trial, 04. The Lancet. 389 Abstract
n/a
Shakur-Still, H, Roberts I, Fawole B, Chaudhri R, El-Sheikh M, Akintan A, Qureshi Z, Kidanto H, Vwalika B, Abdulkadir A, Etuk S, Noor S, Asonganyi Defang E, Alfirevic Z, Beaumont D, Ronsmans C, Arulkumaran S, Grant A, Afsana K, Faye G.  2017.  Effect of early tranexamic acid administration on mortality, hysterectomy, and other morbidities in women with post-partum haemorrhage (WOMAN): An international, randomised, double-blind, placebo-controlled trial, 04. The Lancet. 389 Abstract
n/a
Sharma, A, Alatise OI, Adisa AO, Arowolo OA, Olasehinde O, Famurewa OC, Omisore AD, Komolafe AO, Olaofe O, Katung AI.  2020.  Treatment of colorectal cancer in Sub‐Saharan Africa: Results from a prospective Nigerian hospital registry, 2020. 121(2):342-349. Abstract
n/a
Sharma, A, Alatise O, Adisa A, Arowolo O, Olasehinde O, Famurewa O, Omisore A, Komolafe A, Olaofe O, Katung A, Ibikunle D, Egberongbe A, Olatoke S, Agodirin O, Adesiyun A, Adeyeye A, Ibrahim K, Kolawole O, Idris O, Kingham T.  2019.  Treatment of colorectal cancer in Sub‐Saharan Africa: Results from a prospective Nigerian hospital registry, 11. Journal of Surgical Oncology. 121 Abstract
n/a
Shittu, AK, Mbada KA, Odeyemi TI.  2021.  Evaluating the Impact and Effectiveness of Community-Based Health Insurance Policy Among Informal Sector in Lagos State Using Donabedian Model. International Journal of Public and Private Perspectives on Healthcare, Culture, and the Environment (IJPPPHCE). 5(2):65-80.
Shittu, K, Oyedele D, Babatunde K.  2017.  The effects of moisture content at tillage on soil strength in maize production, 2017/04/01. Egyptian Journal of Basic and Applied Sciences. 4 Abstract
n/a
Shittu, TD, Aransiola EF, Alabi-Babalola OD, others.  2020.  Adsorption Performance of Modified Sponge Gourd for Crude Oil Removal. Journal of Environmental Protection. 11:65., Number 02: Scientific Research Publishing Abstract
n/a
Shittu, O, Raji Y, Osonuga OA, Stephen A, Togun V, Azeez M.  2020.  Age at Menarche and its Predicting Factors in Cities of Ibadan and Ogbomoso of Southwestern Nigeria, 08. Abstract
n/a
Shittu, A, Kuti O, Orji E, Makinde N, Ogunniy S, Ayoola O, Sule S.  2007.  Clinical versus Sonographic Estimation of Foetal Weight in Southwest Nigeria, 2007/04/01. 25:14-23. Abstract

A prospective study was conducted at Obafemi Awolowo University Teaching Hospital Complex, Ile-Ife, Nigeria, between 3 January and 31May 2004, to compare the accuracy of clinical and ultrasonographic estimation of foetal weight at term. One hundred pregnant women who fulfilled the inclusion criteria had their foetal weight estimated independently using clinical and ultrasonographic methods. Accuracy was determined by percentage error, absolute percentage error, and proportion of estimates within 10% of actual birthweight (birthweight of +10%). Statistical analysis was done using the paired t-test, the Wilcoxon signed-rank test, and the chi-square test. The study sample had an actual average birthweight of 3,255+622 (range 2,150–4,950) g. Overall, the clinical method overestimated birthweight, while ultrasound underestimated it. The mean absolute percentage error of the clinical method was smaller than that of the sonographic method, and the number of estimates within 10% of actual birthweight for the clinical method (70%) was greater than for the sonographic method (68%); the difference was not statistically significant. In the low birthweight (<2,500 g) group, the mean errors of sonographic estimates were significantly smaller, and significantly more sonographic estimates (66.7%) were within 10% of actual birthweight than those of the clinical method (41.7%). No statistically significant difference was observed in all the measures of accuracy for the normal birthweight range of 2,500-<4,000 g and in the macrosonic group (≥4,000 g), except that, while the ultrasonographic method underestimated birthweight, the clinical method overestimated it. Clinical estimation of birthweight is as accurate as routine ultrasonographic estimation, except in low-birthweight babies. Therefore, when the clinical method suggests weight smaller than 2,500 g, subsequent sonographic estimation is recommended to yield a better prediction and to further evaluate foetal well-being.

Shiyanbola, RE, A. Olaleye, T. T. Oladokun.  2017.  Effectiveness of Housing Provision Strategies Employed by Members of Real Estate Development Association of Nigeria (REDAN),. :650–764., Ile Ife, Nigeria: Faculty of Environmental Design and Management International Conference,
Shogbesan, GA, Famurewa OC, Ayoola OO, Bolarinwa RA.  2017.  Evaluation of Renal artery Resistive and Pulsatility index in steady state SCD Patients and Controls. West African Journal of Ultrasound. 18, Number 1 Abstract
n/a
Siccardi, M, Rajoli RKR, Curley P, Olagunju A, Moss D, Owen A.  2013.  Physiologically based pharmacokinetic models for the optimization of antiretroviral therapy: recent progress and future perspectives. Future Virology. 8(9):871-90. Abstract

Anti-HIV therapy is characterized by the chronic administration of antiretrovirals (ARVs), and consequently, several problems can arise during the management of HIV-positive patients. ARV disposition can be simulated by combining system data describing a population of patients and in vitro drug data through physiologically based pharmacokinetic (PBPK) models, which mathematically describe absorption, distribution, metabolism and elimination. PBPK modeling can find application in the investigation of clinically relevant scenarios, while providing the opportunity for a better understanding of the mechanisms regulating drug distribution. In this review, we have analyzed the most recent applications of PBPK models for ARVs and highlighted some of the most interesting areas of use, such as drug–drug interaction, pharmacogenetics, factors regulating absorption and tissue penetration, as well as therapy optimization in special populations. The application of the PBPK modeling approach might not be limited to the investigation of hypothetical clinical issues, but could be used to inform future prospective clinical trials.

Siccardi, M, Olagunju A, Curley P, Hobson J, Khoo S, Back D, Owen A.  2013.  Prediction of Etravirine Pharmacogenetics Using a Physiologically Based Pharmacokinetic Approach (Abstract #888), 3-6 March. 20th Conference on Retroviruses and Opportunistic Infections (CROI). , Atlanta, GA, USA Abstract

Background: Etravirine (ETV) is metabolized by CYP3A4 and CYP2C19. A known inhibitor of CYP2C19, omeprazole increases ETV exposure by 41%. Since CYP2C19*2 (rs4244285) can affect CYP2C19 expression there is the potential to alter ETV exposure. We previously showed utility of physiologically based PK (PBPK) models for predicting genetic associations and drug-drug interactions from in vitro data in the absence of clinical data. The aim of this study was to develop a PBPK model for ETV PK and predict effects of CYP2C19*2 in virtual human subjects.

Methods: A new open-source PBPK model was developed with algorithms describing covariance between demographics and organ size, hepatic metabolism, induction of metabolic enzymes, expression, and mechanisms regulating absorption and distribution. In vitro data describing chemical properties as well as absorption, distribution, metabolism, and elimination of ETV were used to simulate ETV PK at 200 mg twice daily in 200 virtual subjects. Simulated PK parameters, such as Ctrough, Cmax, and AUC were compared with observed values from the literature. The impact of CYP2C19*2 on ETV clearance was then determined by altering CYP2C19 expression in the model. All simulations were conducted using the differential equation solver Berkeley Madonna.

Results: Simulated PK variables at steady state (mean ± SD) were Ctrough (293 ± 185 ng/mL), Cmax (363 ± 207 ng/mL), and AUC (4005 ± 2364 ng/mL.h), in agreement with previous clinical PK data: Ctrough (297 ± 391 ng/mL) and AUC (4522 ± 4710 ng/mL.h). Simulated mean ETV clearance (CL/F), volume of distribution, and ka were 59 ± 31 (L/h), 14.9 ± 3.6 L/kg, and 0.17 ± 0.011 hr–1, respectively. ETV (CL/F) was predicted to be 62 ± 35, 53 ± 31, and 41 ± 28 L/h for CYP2C19 *1/*1, *1/*2 and *2/*2, respectively.

Conclusions: The IVIVE model predicted in vivo PK of ETV in individuals with different CYP2C19 genotypes. The frequency of CYP2C19*2 has a higher frequency in Asian populations which may underpin heterogeneity in ETV exposure. Mechanistic evaluation of disposition can inform PBPK models and prediction of pharmacogenetic associations. IVIVE may be particularly helpful for the rational design of novel regimens for use in stratified populations. This includes prediction of optimal dose and dosing regimen, selection of partner drugs and validation of the likely overall pharmacological effect of discrete molecular processes, all of which can and should be tested in clinical studies.

Siccardi, M, Olagunju A, Seden K, Ebrahimjee F, Rannard S, Back D, Owen A.  2013.  Use of a physiologicallybased pharmacokinetic model to simulate artemether dose adjustment for overcoming the drug-drug interaction with efavirenz. In Silico Pharmacology. 1(4) Abstract

PURPOSE: To treat malaria, HIV-infected patients normally receive artemether (80 mg twice daily) concurrently with antiretroviral therapy and drug-drug interactions can potentially occur. Artemether is a substrate of CYP3A4 and CYP2B6, antiretrovirals such as efavirenz induce these enzymes and have the potential to reduce artemether pharmacokinetic exposure. The aim of this study was to develop an in vitro in vivo extrapolation (IVIVE) approach to model the interaction between efavirenz and artemether. Artemether dose adjustments were then simulated in order to predict optimal dosing in co-infected patients and inform future interaction study design.

METHODS: In vitro data describing the chemical properties, absorption, distribution, metabolism and elimination of efavirenz and artemether were obtained from published literature and included in a physiologically based pharmacokinetic model (PBPK) to predict drug disposition simulating virtual clinical trials. Administration of efavirenz and artemether, alone or in combination, were simulated to mirror previous clinical studies and facilitate validation of the model and realistic interpretation of the simulation. Efavirenz (600 mg once daily) was administered to 50 virtual subjects for 14 days. This was followed by concomitant administration of artemether (80 mg eight hourly) for the first two doses and 80 mg (twice daily) for another two days.

RESULTS: Simulated pharmacokinetics and the drug-drug interaction were in concordance with available clinical data. Efavirenz induced first pass metabolism and hepatic clearance, reducing artemether Cmax by 60% and AUC by 80%. Dose increases of artemether, to correct for the interaction, were simulated and a dose of 240 mg was predicted to be sufficient to overcome the interaction and allow therapeutic plasma concentrations of artemether.

CONCLUSIONS: The model presented here provides a rational platform to inform the design for a clinical drug interaction study that may save time and resource while the optimal dose is determined empirically. Wider application of IVIVE could help researchers gain a better understanding of the molecular mechanisms underpinning variability in drug disposition.

Siccardi, M, Olagunju A, Simiele M, D’Avolio A, Calcagno A, Perri GD, Bonora S, Owen A.  2014.  Relative genetic contribution to the pharmacokinetics of commonly prescribed antiretrovirals (Abstract #504), 3-6 March. 21st Conference on Retroviruses and Opportunistic Infections (CROI). , Boston, MA, USA Abstract

Background: Antiretroviral pharmacokinetics is characterised by broad variability influenced by numerous factors affecting absorption, distribution, metabolism and elimination. Recently, a relative genetic contribution (rGC) of 0.904 (0.64 – 0.97) was reported for nevirapine (NVP) AUC0-6h (Micheli et al, Pharmacogenet Genomics, 2013). The aim of this study was to assess the Cmin rGC for a panel of antiretroviral drugs to rank agents according to the degree to which heritability influences their pharmacokinetics.

Methods: Patients from the Therapeutic Drug Monitoring Registries of the University of Turin and the University of Liverpool were included in the study. Inclusion criteria for both cohorts were as follows: receiving boosted lopinavir (LPV/r, 300/100 mg twice daily), boosted atazanavir (ATV/r 300/100 mg once daily), unboosted ATV (ATV, 400mg once daily), efavirenz (EFV, 600 mg once daily), NVP (400 mg once daily) or raltegravir (RAL, 400 mg twice daily), age>18 years, not receiving drugs known to contribute to drug-drug interactions. Plasma drug concentrations were determined using validated HPLC or LC-MS/MS methods. Intrapatient (SDw) and interpatient (SDb) variability were measured in patients with plasma concentrations available from more than one occasion. The rGC was calculated using the following equation: 1-(1/F) where F= SDb2/SDw. Statistical significance for genetic contribution was calculated using F-test, α = 0.05.

Results: A total of 211 patients were included in the study, 37 receiving LPV/r, 24 receiving ATV/r, 24 receiving ATV, 82 receiving EFV, 20 receiving NVP and 24 receiving RAL. SDw and SDb were 38% and 43% for LPV/r (n = 37), 49% and 50% for ATV/r (n = 24), 54% and 104% for ATV (n = 24), 33% and 60% for EFV (n = 82), 19% and 44% for NVP (n = 20), and 81% and 95% for RAL (n = 24), respectively. Mean with 95% CI rGC was calculated to be 0.35 (0.06-0.55) for LPV/r, 0.15 (0-0.6) for ATV/r, 0.55 (0.35 – 0.7) for ATV, 0.78 (0.68 – 0.85) for EFV, 0.82 (0.62-0.91) for NVP and 0.08 (0-0.56) for RAL (Figure). Genetic contribution was statistically significant (p<0.05) for ATV, EFV and NVP.

Discussion: The rank order for genetic contribution to variability in Cmin for the study drugs was NVP > EFV > ATV > LPV/r > ATV/r > RAL indicating class specific differences exist. Interestingly, these data indicate that ritonavir reduces the genetic contribution to variability in ATV Cmin presumably through inhibition of gene products such as CYP3A4 and ABCB1. Drugs with higher rGC scores may represent better candidates for pharmacogenetic studies.

Siccardi, M, Olagunju A, Simiele M, D'Avolio A, Calcagno A, Bonora S, Perri DG, Owen A.  2015.  Classspecific relative genetic contribution for key antiretroviral drugs. Journal of Antimicrobial Chemotherapy. 70(11):3074-9. Abstract

OBJECTIVES: Antiretroviral pharmacokinetics is defined by numerous factors affecting absorption, distribution, metabolism and elimination. Biological processes underpinning drug distribution are only partially characterized and multiple genetic factors generate cumulative or antagonistic interactions, which complicates the implementation of pharmacogenetic markers. The aim of this study was to assess the degree to which heredity influences pharmacokinetics through the quantification of the relative genetic contribution (rGC) for key antiretrovirals.

METHODS: A total of 407 patients receiving lopinavir/ritonavir, atazanavir/ritonavir, atazanavir, efavirenz, nevirapine, etravirine, maraviroc, tenofovir or raltegravir were included. Intra-patient variability (SDw) and inter-patient (SDb) variability were measured in patients with plasma concentrations available from more than two visits. The rGC was calculated using the following equation: 1 - (1 / F) where F = SDb(2) / SDw(2).

RESULTS: Mean (95% CI) rGC was calculated to be 0.81 (0.72-0.88) for efavirenz, 0.74 (0.61-0.84) for nevirapine, 0.67 (0.49-0.78) for etravirine, 0.65 (0.41-0.79) for tenofovir, 0.59 (0.38-0.74) for atazanavir, 0.47 (0.27-0.60) for atazanavir/ritonavir, 0.36 (0.01-0.48) for maraviroc, 0.15 (0.01-0.44) for lopinavir/ritonavir and 0 (0-0.33) for raltegravir.

CONCLUSIONS: The rank order for genetic contribution to variability in plasma concentrations for the study drugs was efavirenz > nevirapine > etravirine > tenofovir > atazanavir > atazanavir/ritonavir > maraviroc > lopinavir/ritonavir > raltegravir, indicating that class-specific differences exist. The rGC strategy represents a useful tool to rationalize future investigations as drugs with higher rGC scores may represent better candidates for pharmacogenetic-pharmacokinetic studies.

Siccardi, M, Olagunju A, Seden K, Ebrahimjee F, Rannard S, Back D, Owen A.  2013.  Use of a physiologically-based pharmacokinetic model to simulate artemether dose adjustment for overcoming the drug-drug interaction with efavirenz. In Silico Pharmacology. 1:4 doi:10.1186/2193-9616-1-4(1:4) AbstractIn Silico Pharmacology website

Purpose

To treat malaria, HIV-infected patients normally receive artemether (80 mg twice daily) concurrently with antiretroviral therapy and drug-drug interactions can potentially occur. Artemether is a substrate of CYP3A4 and CYP2B6, antiretrovirals such as efavirenz induce these enzymes and have the potential to reduce artemether pharmacokinetic exposure. The aim of this study was to develop an in vitro in vivo extrapolation (IVIVE) approach to model the interaction between efavirenz and artemether. Artemether dose adjustments were then simulated in order to predict optimal dosing in co-infected patients and inform future interaction study design.

Methods

In vitro data describing the chemical properties, absorption, distribution, metabolism and elimination of efavirenz and artemether were obtained from published literature and included in a physiologically based pharmacokinetic model (PBPK) to predict drug disposition simulating virtual clinical trials. Administration of efavirenz and artemether, alone or in combination, were simulated to mirror previous clinical studies and facilitate validation of the model and realistic interpretation of the simulation. Efavirenz (600 mg once daily) was administered to 50 virtual subjects for 14 days. This was followed by concomitant administration of artemether (80 mg eight hourly) for the first two doses and 80 mg (twice daily) for another two days.

Results

Simulated pharmacokinetics and the drug-drug interaction were in concordance with available clinical data. Efavirenz induced first pass metabolism and hepatic clearance, reducing artemether Cmax by 60% and AUC by 80%. Dose increases of artemether, to correct for the interaction, were simulated and a dose of 240 mg was predicted to be sufficient to overcome the interaction and allow therapeutic plasma concentrations of artemether.

Conclusions

The model presented here provides a rational platform to inform the design for a clinical drug interaction study that may save time and resource while the optimal dose is determined empirically. Wider application of IVIVE could help researchers gain a better understanding of the molecular mechanisms underpinning variability in drug disposition.

Siccardi, M, Rajoli RKR, Curley P, Olagunju A, Moss D, Owen A.  2013.  Physiologically based pharmacokinetic models for the optimization of antiretroviral therapy: recent progress and future perspective, 2013. Future Virology. 8(9):871-890.: Future Medicine AbstractWebsite

Anti-HIV therapy is characterized by the chronic administration of antiretrovirals (ARVs), and consequently, several problems can arise during the management of HIV-positive patients. ARV disposition can be simulated by combining system data describing a population of patients and in vitro drug data through physiologically based pharmacokinetic (PBPK) models, which mathematically describe absorption, distribution, metabolism and elimination. PBPK modeling can find application in the investigation of clinically relevant scenarios, while providing the opportunity for a better understanding of the mechanisms regulating drug distribution. In this review, we have analyzed the most recent applications of PBPK models for ARVs and highlighted some of the most interesting areas of use, such as drug–drug interaction, pharmacogenetics, factors regulating absorption and tissue penetration, as well as therapy optimization in special populations. The application of the PBPK modeling approach might not be limited to the investigation of hypothetical clinical issues, but could be used to inform future prospective clinical trials.