In addition, it was possible to incorporate the effect of sepsis on the volume of distribution, according to the formulas below:. Inter-individual variability IIV on clearance and volume of distribution was estimated from the available paediatric data in combination with prior parameter distributions based on the estimates obtained by Carlier and colleagues Carlier et al.
Inter-occasion variability IOV was also identified for volume of distribution. The inclusion of IOV allowed us to account for the variability associated with the differences in drug distribution during the course of treatment. The effect of disease was assumed to be time-variant and change nonlinearly during the course of treatment until remission of the symptoms:. All subjects were considered to have responded to treatment to allow the estimation of a parameter relative to the effect of the disease on volume of distribution.
Model building criteria included successful minimization, standard error of estimates and termination of the covariance step. Comparison of hierarchical models was based on the changes to the objective function value OFV.
As allometric scaling was applied to extrapolate parameters across populations, the implementation of a stepwise covariate inclusion and exclusion procedure was not deemed necessary. Outlier detection was initially based on visual examination of individual and study variables.
Goodness-of-fit was assessed by statistical and graphical methods, including population and individual predicted vs. A visual predictive check was utilized to evaluate the adequacy of the final model, including the effects of statistically significant covariates Yano et al. Given that the effect of sepsis on drug disposition varies over time and pharmacokinetic data were collected only at the beginning of treatment in the SATT trials, model performance was evaluated using external data, in which the disposition of amoxicillin was investigated at the end of treatment Weingartner et al.
Six important assumptions are required for the assessment and interpretation of the results from the different simulation scenarios, namely:. Variability in treatment response clinical cure was assumed to be directly linked to variability in pharmacokinetics, rather than bacterial resistance.
To take into account the variability in body weight, each patient was considered to have a weight within the same percentile of the growth curve from birth until completion of the study. Correlations between demographic characteristics and physiological processes associated with drug disposition were treated as constant across the course of disease unless available evidence showed otherwise.
The effect of diarrhea and other gastro-intestinal tract symptoms on the overall rate and extent of absorption of amoxicillin was considered to be minimal after oral administration.
As such, bioavailability estimates were assumed to be similar across the population. Variability in systemic exposure was therefore assumed to be caused primarily by interindividual differences in disposition parameters, rather than bioavailability. In addition, pharmacokinetics was considered to be linear beyond the observed range of concentrations if higher doses i.
This threshold was meant to account for model uncertainty. This figure also takes into account current regulatory guidelines for changes in dosage forms. The effect of variable adherence to treatment not included in the current analysis. Dose missingness is therefore assumed to be at random and compliance to be dose-independent in this population. Amoxicillin exposure following twice daily oral administration was simulated in a hypothetical population of children with ages varying from 0 to 59 days, with similar baseline demographic characteristics of the neonatal patients enrolled into the AFRINEST and SATT trials.
Further details regarding the study design characteristics used across the different simulation scenarios are summarized in Figure 1B. The endpoints of interest in our analysis included the plasma concentration vs. The selection of a simplified regimen according to weight bands was based on evidence of comparable exposure across the target population, while maximizing the number of patients with acceptable time above MIC. Given that amoxicillin is delivered orally, and absorption is rapid, formulation was not considered a significant source of variability in the simulation scenarios.
Frequency and times for pharmacokinetic sampling were based on a serial sampling scheme for the purposes of estimating AUC over the dosing interval. C max and C min were determined, respectively, by the maximum predicted concentration in each dosing interval and the value of predicted concentration immediately before the next dose.
The trapezoidal rule was applied for the integration of the concentration vs. Figure 1C shows the dose and total daily dose evaluated in each scenario. It should be noted that the weight bands included in the current analysis have been restricted to ranges which are aligned with those used for concurrent medications, such as gentamicin. This threshold is based on historical evidence from microbiological, safety and efficacy studies Howie et al.
Likewise, peak concentrations were summarized without a strict cut-off or reference value. Consequently, we have decided not to perform any formal statistical hypothesis testing to compare scenarios, but simply to identify the best performing regimens.
To that purpose, the probability of target attainment was deemed the most suitable criterion for ranking the performance of the different regimens. R version 3.
Our analysis shows how empirical dosing recommendations can be assessed in a systematic manner, taking into consideration the contribution of factors known to affect drug disposition in the neonatal patient population.
Given the objective of this investigation, first a brief overview is provided of the pharmacokinetic modeling results and parameter estimates which were used across the different scenarios. We then present the simulation results. For the sake of clarity, only two scenarios will be discussed in addition to the selected simplified regimen. The second refers to the WHO recommendations for management of possible serious bacterial infections in young infants days old when referral care is not possible.
An overview of the demographic variables included in the clinical trial simulations is presented in Table 2. As shown in Figure S2 model parameterization based on first order absorption and two-compartment disposition allowed the characterization of amoxicillin plasma levels in the target paediatric population. One subject was excluded from the analysis due to significantly higher concentrations than the rest of the population. The deviation met the criteria for outlier data handling.
Despite the relatively small population, in addition to the effect of covariate factors identified as influential on clearance i. Model parameters were estimated without significant correlations and with good precision. In addition, the visual predictive check reveals that amoxicillin plasma concentrations from neonatal sepsis patients enrolled into the SATT study were approximately 5-fold lower than previously reported with comparable doses in age-matched patients with non-systemic infections Figure 3.
An overview of the final model parameters is summarized in Table 3. Individual empirical Bayesian post-hoc parameter estimates are reported in Table S1. It is interesting to highlight that sepsis patients showed a 4-fold increase in the central and peripheral volume of distribution. Figure 3 Comparison between model predictions and observed data. Right plot shows model predictions along with observed amoxicillin concentrations in healthy subjects overlaid with observed exposures in pre-term and term newborns diagnosed with other infections.
Blue lines represent the predicted median concentrations; shaded areas depict the predicted 5 th and 95 th percentiles. The error bars indicate the 5 th and 95 th percentiles the observed data in Weingartner et al. Table 3 Population pharmacokinetic model parameters and bootstrap estimates used to describe the concentration vs. Significant differences were also predicted between first and last dose Figure 4.
Figure 4 Predicted amoxicillin area under the concentration vs. Upper and lower panels show the predictions after the first and last dose, respectively. Figure 6 shows the population predicted plasma concentration vs. These profiles correspond to the systemic exposure ranges shown in Figure 7. As it can be observed, the two regimens seem to overlap considerably with each other. Figure 6 Predicted amoxicillin concentration vs.
Panels show how the proposed two-weight banded regimen compares to the WHO recommended regimen. First dose day 1 and last dose day 7 are shown to highlight the impact of disease on the pharmacokinetics of amoxicillin. Overall the proposed weight-banded regimen results in similar exposure ranges. Figure 7 Predicted amoxicillin AUC in sepsis patients aged 0 to 59 days stratified according to a simplified regimen with two weight bands.
Panels show how the proposed two-weight banded regimen compares with the WHO recommended regimen. All the subjects outside this range are represented by the dots. First dose day 1 and last dose day 7 are shown to illustrate the effect of disease on the pharmacokinetics of amoxicillin. Legend indicates the total daily dose for a b.
Another point to consider when comparing treatment scenarios are the differences in drug levels at the end of the dosing interval. In addition, the PTA was calculated and is shown in Figure 9.
Table 5 Predicted exposure to amoxicillin following administration of and mg doses according to a twice daily regimen. Figure 9 Probability of target attainment PTA in sepsis patients aged 0 to 59 days.
Panels show how the proposed weight-banded regimen compares to the WHO recommended dose. While careful use of antibiotics is still needed in all paediatric settings, appropriate drug selection and dose optimization are essential when referral is not feasible.
Despite the availability of guidelines for managing possible serious bacterial infection in young infants Muller-Pebody et al. Recently, Fuchs and colleagues performed a review of the appropriate empirical therapy for treating sepsis in neonates and children Fuchs et al. The authors focus on the current WHO guidelines supporting the use of gentamicin and penicillin for hospital-based patients or gentamicin IM and amoxicillin oral when referral to a hospital is not possible, and suggest that there is no strong evidence to change them.
Unfortunately, neither this review nor previous ones have evaluated the feasibility of simplified dosing regimens for amoxicillin in neonatal sepsis patients taking into account PKPD principles. Whereas adherence to treatment was also taken into consideration for the selection of the simplest antibiotic regimens that are both safe and effective in children 0—59 days old, it appears that an opportunity has been missed ensure that recommendations are further supported by a scientifically robust dose rationale.
In the current investigation, we have applied quantitative clinical pharmacology methods to identify a simplified regimen for amoxicillin in new-borns and young infants. It has been previously demonstrated that accurate characterization of PKPD relationships allows not only for the selection of the best drug to treat a specific bacterial pathogen, but also enables the optimization of the dosing regimen Bhavnani et al.
In spite of the widespread use of amoxicillin in paediatric infections, pharmacokinetic data in neonates with serious bacterial infections are rather sparse Ginsburg et al. In reality, among the recent studies in neonatal sepsis, blood samples for pharmacokinetic analysis have been collected only in the SATT trial Mir, This limitation is partly overcome by evolving understanding of paediatric pharmacology, which shows that age maturation and weight-related differences in renal function ultimately determine the observed changes in the pharmacokinetics of amoxicillin in neonates.
Evidence from other drugs suggests that any attempt to define the dose rationale in this population will also need to consider the contribution of factors such as critical illness, obesity and immune deficiency, which often compound the effect of age and weight Levison and Levison, ; Suzuki et al. Surprisingly, the population pharmacokinetics of amoxicillin has never been investigated in neonatal sepsis.
As a consequence, we have had to resort to bridging and extrapolation concepts to describe drug exposure in this population. In this context, we have applied an integrated approach to ensure that organ maturation, developmental growth and disease-related factors were considered. While the model developed by Carlier and colleagues Carlier et al. The use of aminoglycoside clearance as a marker of the renal processes associated with drug elimination represented a practical solution Zhao et al.
In fact, the work by Zhao et al. Moreover, the amikacin maturation model enabled reasonable prediction of the clearance of vancomycin, which similarly to amoxicillin, is also excreted by tubular mechanisms Contrepois et al.
Their results show that prediction bias was not significantly correlated with developmental factors e. In contrast to most investigations in paediatric clinical pharmacology, where maturation and size are usually explanatory factors for the differences in drug disposition in new-borns and young infants, our analysis also sheds light into the magnitude of the effect of disease-related changes e.
In fact, the impact of sepsis on systemic exposure only became evident after careful evaluation of sparse sampled data from patients in the SATT study. Differently from the findings in critically ill adult patients Carlier et al. The observed differences reflect the pathophysiology of serious bacterial infections. Endothelial damage provoked by systemic inflammatory response syndrome SIRS may result in an increase in capillary permeability and interstitial edema formation, all of which ultimately affect the volume of distribution De Paepe et al.
In addition, there is no evidence in the clinical literature to suggest that the proposed dosing regimen would represent an increased risk of renal toxicity e. Hence, the use of weight-banded dosing represents a major opportunity for the treatment of neonatal sepsis in resource-limited settings.
In other words, the synthesized polymer should be nontoxic to normal body cells and tissues, and cause minimum side effects at the site of action. There are different types of tests and assays for the evaluation of cytotoxicity of polymers, as well as drugs.
After stirring for 15 minutes at room temperature, the solvent needs to be evaporated by rotary evaporator. The precipitant is then mixed with 20 ml distilled water. The mixture is then centrifuged at rpm for 10 minutes.
The supernatant is then taken for further analysis for entrapment characteristics of the drug in the polymer. In order to obtain the entrapment efficiency, the concentration of the free drug is to be determined upon preparation of the entrapment, 1 ml of the supernatant is taken and diluted with 3 ml water, and the concentration of the drug is determined by high performance liquid chromatography HPLC.
Entrapment efficiency is calculated by the following equation:. The polydispersity index PDI is a reflection of the heterogeneity and a measure of the distribution of molecular mass in a given polymer sample.
PDI is calculated as the weight average molecular weight, divided by the number of average molecular weight. It indicates the distribution of individual molecular masses in a batch of polymers. PDI value of 1 reflects that the polymer is of the same size and indicates uniformity of the chain length.
The following equation denotes the PDI:. DLS is used for determining the size distribution and zeta potential of nanoparticles as well. Dynamic light scattering, which is also known as photon correlation spectroscopy, is one of the most widely used methods for the determination of size, size distribution, and zeta potential of nanoparticles. This instrument works through radiation of a light beam into a particulate system with Brownian motion.
Differential scanning calorimetry DSC technique is the most common thermal analysis equipment used in the determination of material in the delivery system. This primary technique directly assesses the uptake of heat energy during the fluctuation of temperature in order to specify any connection among temperature and physical properties of samples. Calorimetry is a suitable thermal analysis technique for qualifying the purity, the melting point, and the polymorphic forms of samples [ 21 ]. Drug release from the polymeric system shall be studied to prove good delivery as stipulated.
Commonly, the in vitro dissolution of the drug from the formulation is done following the available compendium method where standard dissolution apparatus are recommended. Other methods include using dialysis method where the formulation prepared is placed in the dialysis bag. Samples were collected at different time intervals and analyzed.
This is one of the stages for preclinical study on the new formulation which can also be a new type of polymer or material used [ 19 ]. The safety and efficacy of this formulation need to be established.
Before starting the study, the animal ethic committee needs to be consulted to get approval to start the study. Most of the studies are to prove that the pharmacokinetics of the drug delivered is appropriate as stipulated. The ADME Absorption, Distribution, Metabolism, and Excretion of the drug delivered by the system is important at this stage, especially the absorption and distribution.
For the technique in determining the absorption and the distribution of the active in a formulation, a researcher may in his or her study use optical in vivo imaging technique for monitoring the distribution of the drug in question the proposed delivery system in comparison with the conventional dosage form available.
This technique is able to image the whole body of small animals and body cells. In fluorescence microscopy, the objects of imaging are cells, slides, or culture dishes, while the whole body of small animals is pictured with optical in vivo imaging system. Furthermore, it is essential to apply an appropriate imaging probe, which provides biologically stable distribution and preferential accumulation at the intended target site.
Researcher performing the animal study should also take the opportunity to do plasma level drug monitoring, urine metabolite level, and histological studies on heart, lungs, kidneys, spleen, and the liver.
This is a regulatory requirement as to prove that the new system will make the drug available as the conventional system. It indirectly also determines if the drug pharmacokinetic parameters in human are the same as for the original available formulation.
This is different from bioequivalence, which is used to evaluate the predictable in vivo biological equivalence of two proprietary preparations of a drug. Two pharmaceutical products are bioequivalent if they are pharmaceutically equivalent and their bioavailabilities after administration in the same dose are similar to such a degree that their effects, with respect to both efficacy and safety.
Bioavailability measures the extent of a drug reaching the systemic circulation and is therefore available for action at the expected site. For most drugs that are taken orally, the drug is released in the gastrointestinal GI tract and arrives at their site of action via the systemic circulation. Plasma concentrations of the drug or its metabolite would provide a marker for the concentration at the site of action and a valid measure of bioavailability.
The researcher needs to build a plasma blood concentration time curve to prove the release of the drug from the preparation and its absorption from the GI tract, but also other factors including presystemic metabolism, distribution, and elimination. Bioavailability is proven through the area under the blood drug concentration versus time curve AUC , the maximum blood concentration C max and the time to reach maximum concentration T max.
Clearly, bioavailability studies of the new delivery systems compared to the conventional ones need to be done so as to be assured that the new delivery system is not inferior compared to the existing systems. Drug delivery system represents a vast, vital area of research and development of new analgesic product.
It is pertinent for analgesic as pain management needs the painkiller to be fast in action, prolong action, and reduce adverse or side effect. So development of specialty product using advance drug release system is the answer to the betterment of pain management and the research on this area is not exhaustive.
In this chapter, we have discussed the available conventional dosage forms and gave examples. We also based our discussions on ideas in research and development of various advance new delivery system such as polymeric delivery system, sustain release system, transdermal delivery system, and liposome.
Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3. Help us write another book on this subject and reach those readers. Login to your personal dashboard for more detailed statistics on your publications. Edited by Cecilia Maldonado. Edited by Ali Demir Sezer. Boateng and Martin J. We are IntechOpen, the world's leading publisher of Open Access books. Built by scientists, for scientists.
Our readership spans scientists, professors, researchers, librarians, and students, as well as business professionals. Downloaded: Abstract Drugs including analgesics need a delivery system to deliver it to the site of action upon administration.
Keywords analgesic pain management modified drug delivery system specialty product and polymer. Introduction Analgesics are medicines that relieve pain or in other words they are drugs that are used to provide pain relief. Chronic pain Chronic pain is defined as pain lasting over 3 months and severe enough to have effect on body function.
Narcotic analgesics Narcotic analgesics are all derived from opium. Conventional dosage forms of analgesics Conventional dosage forms of analgesic are the same as any conventional dosage form of general pharmaceuticals.
Type of pain killer in the market Common dosage form available 1. Paracetamol acetaminophen Tablets, solution, suspension, suppository, injection 2. Paracetamol with codiene Tablets, solution, suspension 3. Celecoxib Capsules 4. Diclofenac Tablets, capsules, gel local application 5. Hydrocodone Tablets, elixer 7. Hydrocodone with paracetamol Tablets, elixer 8. Hydromorphone Tablets, injection, suppositories, liquid 9.
Ibuprofen Tablets, solution, suspension Meloxicam Tablets, oral suspension Methadone Tablets, oral solution, oral concentrate, injection Milnacipran Tablets, injection Morphine Tablets, injection Oxycodone Tablets, oral concentrate, oral solution Oxycodone with paracetamol Tablets Table 1.
Some of the analgesic and their dosage form available in the market. Research in the development of new delivery system with existing analgesic Development of modified release painkiller is a popular research. The polymeric delivery system: polymers in controlled drug delivery The use of various polymers in controlled drug delivery is very popular among formulation researchers. Table 2. Example of synthetic polymer available in the market.
Table 3. Example of natural polymer used in drug delivery research. Iontophoresis An active state of transdermal technologies uses low voltage electrical current to drive charged drugs through the skin. The information contained in this web site is intended for US healthcare professionals only.
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