Individualization of drug therapy: history, present state, and opportunities for the future

Quality by Design Considerations for Drop-on-Demand Point-of-Care Pharmaceutical Manufacturing of Precision Medicine

Distributed and point-of-care (POC) manufacturing facilities enable an agile pharmaceutical production paradigm that can respond to localized needs, providing personalized and precision medicine. These capabilities are critical for narrow therapeutic index drugs and pediatric or geriatric dosing, among other specialized needs. Advanced additive manufacturing, three-dimensional (3D) printing, and drop-on-demand (DoD) dispensing technologies have begun to expand into pharmaceutical production. We employed a quality by design (QbD) approach to identify critical quality attributes (CQAs), critical material attributes (CMAs), and critical process parameters (CPPs) of a POC pharmaceutical manufacturing paradigm. This theoretical framework encompasses the production of active pharmaceutical ingredient (API) "inks" at a centralized facility, which are distributed to POC sites for DoD dispensing into/onto delivery vehicles (e.g., orodispersible films, capsules, single liquid dose vials). Focusing on the POC dispensing/dosing processes, QbD considerations and cause-and-effect analyses identified the dispensed API quantity and solid-state form (CQAs), as well as the nozzle diameter, system pressure channel, and number of drops dispensed (CPPs) for detailed investigation. Final assay quantification and content uniformity CQAs were measured from demonstrative levothyroxine sodium single-dose liquid vials of glycerin/water, meeting the standard acceptance values. Each POC facility is unlikely to maintain full quality control laboratory capabilities, requiring the development of appropriate atline or inline methods to ensure quality control. We developed control strategies, including atline ultraviolet-visible (UV-vis) verification of the API ink prior to dispensing, inline drop counting during dispensing, intermediate atline-dispensed volume checks, and offline batch confirmation by liquid chromatography-tandem mass spectrometry (LC-MS/MS) following production.

Pharmacological aspects of antiseizure medications: From basic mechanisms to clinical considerations of drug interactions and use of therapeutic drug monitoring

Antiseizure medications (ASMs) are the cornerstone of treatment for patients with epilepsy. Several new ASMs have recently been introduced to the market, making it possible to better tailor the treatment of epilepsy, as well as other indications (psychiatry and pain disorders). For this group of drugs there are numerous pharmacological challenges, and updated knowledge on their pharmacodynamic and pharmacokinetic properties is, therefore, crucial for an optimal treatment outcome. This review focuses on educational approaches to the following learning outcomes as described by the International League Against Epilepsy (ILAE): To demonstrate knowledge of pharmacokinetics and pharmacodynamics, drug interactions with ASMs and with concomitant medications, and appropriate monitoring of ASM serum levels (therapeutic drug monitoring, TDM). Basic principles in pharmacology, pharmacokinetic variability, and clinically relevant approaches to manage drug interactions are discussed. Furthermore, recent improvements in analytical technology and sampling are described. Future directions point to the combined implementation of TDM with genetic panels for proper diagnosis, pharmacogenetic tests where relevant, and the use of biochemical markers that will all contribute to personalized treatment. These approaches are clinically relevant for an optimal treatment outcome with ASMs in various patient groups.

Factors Associated with Increased Health-Related Quality of Life Benefits in Patients with Hereditary Transthyretin Amyloidosis with Polyneuropathy (ATTRv-PN) Treated with Inotersen

INTRODUCTION/AIMS

Hereditary transthyretin amyloidosis with polyneuropathy (ATTRv-PN) is a genetic condition associated with significant morbidity and mortality. We aimed to identify patient subgroups exhibiting the greatest health-related quality of life [HRQL] benefit from inotersen treatment.

METHODS

We examined data from the inotersen phase 2/3 randomized controlled trial for ATTRv-PN, NEURO-TTR (NCT01737398, 66 weeks). LASSO regression models predicted changes in Norfolk QoL-DN total score (TQoL, range -4 to 136; higher scores indicate poorer HRQL) from baseline in the inotersen and placebo arm, respectively. Individualized efficacy scores (ES) were calculated as differences between predicted change-scores had patients received inotersen vs. placebo. Patients were ranked by ES to define the greatest-benefit subpopulation (top 50%). Characteristics of the top 50% and bottom 50% of patients were compared.

RESULTS

The overall mean ± standard deviation TQoL change was -0.20±19.13 for inotersen (indicating no change) and 10.77±21.13 for placebo (indicating deterioration). Within the highest-benefit patients, mean TQoL change was -11.03±17.06 (improvement) for inotersen and 11.24±22.97 (deterioration) for placebo (P<0.001). Compared with the overall population, patients in the greatest-benefit subpopulation were younger, more likely to have polyneuropathy disability (PND) scores 1 or 2, less likely to have received prior tafamidis or diflunisal treatment, and more likely to have Val30Met mutations and higher (worse) baseline TQoL.

CONCLUSION

Patients who were younger and/or at earlier polyneuropathy stages experienced greater HRQL benefits from inotersen over 66 weeks. These findings underscore the need for early diagnosis and treatment initiation, especially among more severely affected patients in early stages of ATTRv-PN. This article is protected by copyright. All rights reserved.

Dose Banding – weighing up benefits, risks and therapeutic failure

Aims

Dose banding is a method of dose individualisation in which all patients with similar characteristics are allocated to the same dose. Dose banding results in some patients receiving less intensive treatment which risks a reduction in therapeutic benefit (iatrogenic therapeutic failure) because of variability not predicted by dose banding. This study aims to explore the effects of dose banding on therapeutic success and failure.

Methods

This was a simulation study. Virtual patients were simulated under a simple pharmacokinetic model where the response of interest is the steady‐state average concentration. Clearance was correlated with a covariate used for dose banding. Dose individualisation was based on: one‐dose‐fits‐all, covariate‐based dosing, empirical dose banding, dose banding optimised for net therapeutic benefit and optimised for both benefit and minimising iatrogenic therapeutic failure.

Results

The lowest and highest probability of target attainment (PTA) were 44% for one‐dose‐fits‐all and 72% for covariate‐based dosing. Neither dosing approach would result in iatrogenic therapeutic failure as lower dose intensities do not occur. Empirical dose banding performed better than one‐dose‐fits‐all with 59% PTA but not as good as either optimised method (64–69% PTA) while carrying a risk of iatrogenic therapeutic failure in 25% of patients. Optimising for benefit (only) improved PTA but carried a risk of iatrogenic therapeutic failure of up to 10%. Optimising for benefit and minimising iatrogenic therapeutic failure provided the best balance.

Conclusion

Future application of dose banding needs to consider both the probability of benefit as well the risk of causing iatrogenic therapeutic failure.

Physiologically based pharmacokinetic modeling of candesartan related to CYP2C9 genetic polymorphism in adult and pediatric patients

Candesartan cilexetil is an angiotensin II receptor blocker and it is widely used to treat hypertension and heart failure. This drug is a prodrug that rapidly converts to candesartan after oral administration. Candesartan is metabolized by cytochrome P450 2C9 (CYP2C9) enzyme or uridine diphosphate glucurinosyltransferase 1A3, or excreted in an unchanged form through urine, biliary tract and feces. We investigated the effect of genetic polymorphism of CYP2C9 enzyme on drug pharmacokinetics using physiologically based pharmacokinetic (PBPK) modeling. In addition, by introducing the age and ethnicity into the model, we developed a model that can propose an appropriate dosage regimen taking into account the individual characteristics of each patient. To evaluate the suitability of the model, the results of a clinical trial on twenty-two healthy Korean subjects and their CYP2C9 genetic polymorphism data was applied. In this study, PK-Sim® was used to develop the PBPK model of candesartan.

Chronopharmacology in Therapeutic Drug Monitoring-Dependencies between the Rhythmics of Pharmacokinetic Processes and Drug Concentration in Blood

The objective of the optimization of pharmacotherapy compliant with the basic rules of clinical pharmacology is its maximum individualization, ensuring paramount effectiveness and security of the patient's therapy. Thus, multiple factors that are decisive in terms of uniqueness of treatment of the given patient must be taken into consideration, including, but not limited to, the patient's age, sex, concomitant diseases, special physiological conditions (e.g., pregnancy, lactation, extreme age groups), polypharmacotherapy and polypragmasia (particularly related to increased risk of drug interactions), and patient's phenotypic response to the administered drug with possible genotyping. Conducting therapy while monitoring the concentration of certain drugs in blood (Therapeutic Drug Monitoring; TDM procedure) is also one of the factors enabling treatment individualization. Furthermore, another material, and yet still a marginalized pharmacotherapeutic factor, is chronopharmacology, which indirectly determines the values of drug concentrations evaluated in the TDM procedure. This paper is a brief overview of chronopharmacology, especially chronopharmacokinetics, and its connection with the clinical interpretation of the meaning of the drug concentrations determined in the TDM procedure.

Utility, promise, and limitations of liquid chromatography-mass spectrometry-based therapeutic drug monitoring in precision medicine

Therapeutic drug monitoring (TDM) is typically referred to as the measurement of the concentration of drugs in patient blood. Although in the past, TDM was restricted to drugs with a narrow therapeutic range in order to avoid drug toxicity, TDM has recently become a major tool for precision medicine being applied to many more drugs. Through compensating for interindividual differences in a drug's pharmacokinetics, improved dosing of individual patients based on TDM ensures maximum drug effectiveness while minimizing side effects. This is especially relevant for individuals that present a particularly high intervariability in pharmacokinetics, such as newborns, or for critically/severely ill patients. In this article, we will review the applications for and limitations of TDM, discuss for which patients TDM is most beneficial and why, examine which techniques are being used for TDM, and demonstrate how mass spectrometry is increasingly becoming a reliable and convenient alternative for the TDM of different classes of drugs. We will also highlight the advances, challenges, and limitations of the existing repertoire of TDM methods and discuss future opportunities for TDM-based precision medicine.

Dosage individualization proposed for anti-gout medications among the patients with gout

BACKGROUND

The conventional one-size-fits-all approach has been criticized for almost all drugs used especially for chronic diseases, including gout. The present study was aimed to explore the need of individualization and optimization of the dose of anti-gout medications among gout patients.

METHODS

Cross-sectional study was carried out among 384 randomly selected new gout patients visiting two gout treatment centers at Lalitpur Metropolitan City, Nepal and who were taking antigout medications. Patients not taking anti-gout medications and not showing willingness to participate were excluded. The eGFR was calculated with the CKD Epidemiology Collaboration (CKD-EPI) creatinine equation (2009). Doses to be individualized were decided based on the Renal Drug Handbook and verified with the BNF 80. Data were analyzed via R 4.0.3 by applying the multinomial logistic regression to analyze statistical significance of risk with various predictors, and considering a p-value <0.05 statistically significant. Comorbidities were coded as per the ICD-11 coding and medicines were coded according to the WHO Guidelines for ATC classification and DDD assignment 2020.

RESULTS

The high risk of progression to CKD increased in the age range 54-63 and ≥84 years by 17.77 and 43.02 times, respectively. Also, high risk increased by 29.83 and 20.2 times for the overweight and the obese respectively. Aceclofenac 100mg was prescribed for maximum patients (30.5%). Need of dose individualization was realized in 30 patients, with maximum (7) in case of etoricoxib 90mg. Various glucocorticoids were prescribed for 36.9% patients, out of whom 3.8%required dose individualization and 15.9% patients with xanthine oxidase inhibitors, out of whom 1.3% required dose individualization.

CONCLUSION

Thirty cases required dose individualization, which was although minimal but could have meaningful impact on the clinical success of the individual patient. Based on the recommendation on dose individualization, those patients could be optimized on their therapy on future follow ups.

Data-driven personalization of a physiologically based pharmacokinetic model for caffeine: A systematic assessment

Physiologically based pharmacokinetic (PBPK) models have been proposed as a tool for more accurate individual pharmacokinetic (PK) predictions and model‐informed precision dosing, but their application in clinical practice is still rare. This study systematically assesses the benefit of using individual patient information to improve PK predictions. A PBPK model of caffeine was stepwise personalized by using individual data on (1) demography, (2) physiology, and (3) cytochrome P450 (CYP) 1A2 phenotype of 48 healthy volunteers participating in a single‐dose clinical study. Model performance was benchmarked against a caffeine base model simulated with parameters of an average individual. In the first step, virtual twins were generated based on the study subjects' demography (height, weight, age, sex), which implicated the rescaling of average organ volumes and blood flows. The accuracy of PK simulations improved compared with the base model. The percentage of predictions within 0.8‐fold to 1.25‐fold of the observed values increased from 45.8% (base model) to 57.8% (Step 1). However, setting physiological parameters (liver blood flow determined by magnetic resonance imaging, glomerular filtration rate, hematocrit) to measured values in the second step did not further improve the simulation result (59.1% in the 1.25‐fold range). In the third step, virtual twins matching individual demography, physiology, and CYP1A2 activity considerably improved the simulation results. The percentage of data within the 1.25‐fold range was 66.15%. This case study shows that individual PK profiles can be predicted more accurately by considering individual attributes and that personalized PBPK models could be a valuable tool for model‐informed precision dosing approaches in the future.

Relationship of hemoglobin level and plasma coproporphyrin-I concentrations as an endogenous probe for phenotyping OATP1B

Plasma coproporphyrin‐I (CP‐I) concentration is used as a sensitive and selective endogenous probe for phenotyping organic anion transporting polypeptides 1B (OATP1B) activity in many studies. CP‐I is produced in the process of heme synthesis, but the relationship between plasma CP‐I concentrations and heme synthesis activity is unknown. In this study, we evaluated the relationship between plasma CP‐I concentration and hemoglobin level as a biomarker of heme synthesis activity. The data of 391 subjects selected from the Japanese general population were analyzed. One hundred twenty‐six participants had OATP1B1*15 allele, 11 of whom were homozygous (OATP1B1*15/*15). Multiple regression analysis identified hemoglobin level as an independent variable associated with plasma CP‐I concentration (p < 0.0001). A significant positive correlation was observed between hemoglobin level and plasma CP‐I concentration in participants without OATP1B1*15 allele (n = 265; r_s = 0.35, p < 0.0001) and with OATP1B1*15 allele (n = 126; r_s =0.27, p = 0.0022). However, Kruskal–Wallis test showed no large difference in Kruskal–Wallis statistics between the distribution of plasma CP‐I concentrations and that of ratio of plasma CP‐I to hemoglobin among six OATP1B1 polymorphism groups. These findings suggest that the hemoglobin level seems to reflect biosynthesis of CP‐I. However, correction by hemoglobin level is not required when using basal plasma CP‐I concentration for phenotyping OATP1B activity.

A Critique of Pharmacokinetic Calculators for Drug Dosing Individualization

The 'one-dose-fits-all' approach where drug dosing regimen is prescribed according to recommendations from a summary of product characteristics is not appropriate for many patients whose clinical characteristics significantly differ from the most frequent ones in a population, as it cannot guarantee optimal exposure of target tissues to the drug. Our aim here is to provide a concise review of pharmacokinetic calculators currently available for clinical use and, at the same time, to suggest the minimum standards that they should satisfy to be routinely used in clinical practice. A systematic search of Medline, Ebsco, Scopus, Scindeks, Cochrane Library and Google Scholar was performed to find publications about available pharmacokinetic calculators for drug dose individualization. Theoretically well-founded and mathematically correct calculators for many drugs are available, but only a few calculators for specific drugs have been validated in clinical practice or through clinical trials, and the results published in peer-reviewed journals. The majority of available pharmacokinetic calculators for drug dosing individualization remain unvalidated, i.e., there is no evidence of their efficacy and safety in real-life clinical settings. Pharmacokinetic calculators for drug dose individualization are irreplaceable tools for achieving precision medicine, where dosing regimens are tailored to the needs and personal characteristics of each patient, maximizing efficacy and minimizing toxicity.

The clinical and therapeutic challenge of treating older patients in clinical practice

Due to the demographic shift complex care management of older multimorbid patients with changing functional capacities has become core clinical business for many stakeholders in western health care systems. It is the aim of the mini-review to summarise evidence to be translated into clinical practice for pharmacists and medical doctors and interested readers. The review is based upon a comprehensive literature review in PubMed and EMBASE from 2000 to 2018 and grey literature. Interprofessional exchange and discussion among stakeholders from geriatric medicine and the International Association for Pharmaceutical Technology during a meeting in Graz, Austria 2018, led to the narrowing of the review addressing complex care needs of geriatric patients. In this mini-review, attention is drawn to a comprehensive therapeutic goal setting according to evidence-based guidelines: clinical, disease-related care aspects, functional capacities, evaluated by comprehensive geriatric assessment, and patient's wishes and perspectives as main drivers for personalised complex care of geriatric patients.

Clinical implementation of pharmacogenetics and model-informed precision dosing to improve patient care

Providing maximal therapeutic efficacy without toxicity is a universal goal of rational drug therapy. However, substantial between-patient variability in drug response often impedes such successful treatments and brings the necessity of tailoring drug dose to individual needs for more precise therapy. In many cases plenty of patient characteristics, such as body size, genetic makeup and environmental factors, need to be taken into consideration to find the optimal dose in clinical practice. A pharmacokinetics and pharmacodynamics (PK/PD) model-informed approach offers integration of various patient information to provide an expectation of drug response and derive practical dose estimates to support clinicians' dosing decisions. Such an approach was pioneered in the late 1970s, but its broad clinical acceptance and implementation have been hampered by the lack of widespread computer technology, including user-friendly software tools. This has significantly changed in recent years. With the advent of electronic health records (EHRs) and the ubiquity of user-friendly software tools, we now experience a convergence of clinical information, pharmacogenetics, systems pharmacology and pharmacometrics, and technology. Advanced pharmacometrics research is now more appliable and implementable to improve health care. This article presents examples of successful development and implementation of pharmacogenetics-guided and PK/PD model-informed decision support to facilitate precision dosing, including the development of an EHR-embedded decision support tool. Through the integration of clinical decision support tools in EHRs, clinical pharmacometrics support can be brought directly to the clinical team and the bedside.

Precision Dosing Priority Criteria: Drug, Disease, and Patient Population Variables

The administered dose of a drug modulates whether patients will experience optimal effectiveness, toxicity including death, or no effect at all. Dosing is particularly important for diseases and/or drugs where the drug can decrease severe morbidity or prolong life. Likewise, dosing is important where the drug can cause death or severe morbidity. Since we believe there are many examples where more precise dosing could benefit patients, it is worthwhile to consider how to prioritize drug-disease targets. One key consideration is the quality of information available from which more precise dosing recommendations can be constructed. When a new more precise dosing scheme is created and differs significantly from the approved label, it is important to consider the level of proof necessary to either change the label and/or change clinical practice. The cost and effort needed to provide this proof should also be considered in prioritizing drug-disease precision dosing targets. Although precision dosing is being promoted and has great promise, it is underutilized in many drugs and disease states. Therefore, we believe it is important to consider how more precise dosing is going to be delivered to high priority patients in a timely manner. If better dosing schemes do not change clinical practice resulting in better patient outcomes, then what is the use? This review paper discusses variables to consider when prioritizing precision dosing candidates while highlighting key examples of precision dosing that have been successfully used to improve patient care.

The Steps to Therapeutic Drug Monitoring: A Structured Approach Illustrated With Imatinib

Pharmacometric methods have hugely benefited from progress in analytical and computer sciences during the past decades, and play nowadays a central role in the clinical development of new medicinal drugs. It is time that these methods translate into patient care through therapeutic drug monitoring (TDM), due to become a mainstay of precision medicine no less than genomic approaches to control variability in drug response and improve the efficacy and safety of treatments. In this review, we make the case for structuring TDM development along five generic questions: 1) Is the concerned drug a candidate to TDM? 2) What is the normal range for the drug's concentration? 3) What is the therapeutic target for the drug's concentration? 4) How to adjust the dosage of the drug to drive concentrations close to target? 5) Does evidence support the usefulness of TDM for this drug? We exemplify this approach through an overview of our development of the TDM of imatinib, the very first targeted anticancer agent. We express our position that a similar story shall apply to other drugs in this class, as well as to a wide range of treatments critical for the control of various life-threatening conditions. Despite hurdles that still jeopardize progress in TDM, there is no doubt that upcoming technological advances will shape and foster many innovative therapeutic monitoring methods.

Novel genetic and epigenetic factors of importance for inter-individual differences in drug disposition, response and toxicity

Individuals differ substantially in their response to pharmacological treatment. Personalized medicine aspires to embrace these inter-individual differences and customize therapy by taking a wealth of patient-specific data into account. Pharmacogenomic constitutes a cornerstone of personalized medicine that provides therapeutic guidance based on the genomic profile of a given patient. Pharmacogenomics already has applications in the clinics, particularly in oncology, whereas future development in this area is needed in order to establish pharmacogenomic biomarkers as useful clinical tools. In this review we present an updated overview of current and emerging pharmacogenomic biomarkers in different therapeutic areas and critically discuss their potential to transform clinical care. Furthermore, we discuss opportunities of technological, methodological and institutional advances to improve biomarker discovery. We also summarize recent progress in our understanding of epigenetic effects on drug disposition and response, including a discussion of the only few pharmacogenomic biomarkers implemented into routine care. We anticipate, in part due to exciting rapid developments in Next Generation Sequencing technologies, machine learning methods and national biobanks, that the field will make great advances in the upcoming years towards unlocking the full potential of genomic data.

Handling interoccasion variability in model-based dose individualization using therapeutic drug monitoring data

AIMS

This study aims to assess approaches to handle interoccasion variability (IOV) in a model-based therapeutic drug monitoring (TDM) context, using a population pharmacokinetic model of coagulation factor VIII as example.

METHODS

We assessed 5 model-based TDM approaches: empirical Bayes estimates (EBEs) from a model including IOV, with individualized doses calculated based on individual parameters either (i) including or (ii) excluding variability related to IOV; and EBEs from a model excluding IOV by (iii) setting IOV to zero, (iv) summing variances of interindividual variability (IIV) and IOV into a single IIV term, or (v) re-estimating the model without IOV. The impact of varying IOV magnitudes (0-50%) and number of occasions/observations was explored. The approaches were compared with conventional weight-based dosing. Predictive performance was assessed with the prediction error percentiles.

RESULTS

When IOV was lower than IIV, the accuracy was good for all approaches (50^th percentile of the prediction error [P50] <7.4%), but the precision varied substantially between IOV magnitudes (P97.5 61-528%). Approach (ii) was the most precise forecasting method across a wide range of scenarios, particularly in case of sparse sampling or high magnitudes of IOV. Weight-based dosing led to less precise predictions than the model-based TDM approaches in most scenarios.

CONCLUSIONS

Based on the studied scenarios and theoretical expectations, the best approach to handle IOV in model-based dose individualization is to include IOV in the generation of the EBEs but exclude the portion of unexplained variability related to IOV in the individual parameters used to calculate the future dose.

Twenty Years with Personalized Medicine: Past, Present, and Future of Individualized Pharmacotherapy

On April 16, 1999, a short article appeared in The Wall Street Journal entitled "New Era of Personalized Medicine: Targeting Drugs for Each Unique Genetic Profile," and here, the public was introduced to the term "personalized medicine" for the first time. A few months after publication of the article, it was reprinted in The Oncologist. The article describes the formation of the Single Nucleotide Polymorphisms Consortium, which was established as a collaboration between a number of major pharmaceutical companies and several academic research institutions, with support from the Wellcome Trust Foundation. Reading the article today, one will find that several of the important arguments for an individualized therapy are described in a similar way as we have known it from the past 20 years of discussion. The article mentioned the poor efficacy of the current pharmacotherapy, disease heterogeneity, and genetic variability, a showdown with the "one-size-fits-all" approach, and the use of predictive safety and efficacy biomarkers. Today, personal medicine is in competition with other terms such as "precision medicine" and "stratified medicine" and is no longer the preferred term for describing the individualized health care approach. Even though personalized medicine arose from the idea of improving and individualizing pharmacotherapy, the concept has influenced most other areas of our health care system. No matter if we use the term precision medicine or personalized medicine, the ideas that originated 20 years ago have greatly impacted the way we develop and implement new initiatives in relation to diagnosis, prevention, and treatment today. IMPLICATIONS FOR PRACTICE: Since the publication of the ideas behind personalized medicine in The Wall Street Journal and The Oncologist 20 year ago, they have permeated medical research and innovation. This review will provide an overview of the background, definitions, and terminology and will describe some of the achievements in relation to the treatment of malignant diseases.

Discontinuities and disruptions in drug dosage guidelines for the paediatric population

AIMS

This study investigates paediatric drug dosage guidelines with the aim of investigating their agreement with body surface area (BSA) scaling principles.

METHODS

A total of 454 drug dosage guidelines listed in the AMH-CDC 2015 were examined. Data extracted included the administration, frequency and dose per age bracket from 0 to 18 years. Drug treatments were categorized as follows: (1) The same dose recommendation in milligrams per kilogram (mg kg^-1 ) for all age/weights; (2) Change in the mg kg^-1 dosing according to age/weight; (3) Change in dose in mg according to age/weight; (4) Change from mg kg^-1 dosing to a dose in mg according to age/weight; (5) The same recommendation for all age/weight groups in mg; or (6) BSA dosing. Example drugs were selected to illustrate dose progression across ages.

RESULTS

Most drug treatments (63%) have the same mg kg^-1 dose for all age/weight groups, 14% are dosed in mg kg^-1 across all ages with dose changes according to age/weight, 13% were dosed in mg across all ages with dose changes, 10% switched from mg kg^-1 to a set dose in mg, 4.2% have the same dose in mg for all age and weight groups and 2.2% are dosed according to BSA.

CONCLUSIONS

Paediatric dosage guidelines are based on weight-based formulas, available dosing formulations and prior patterns of use. Substantial variation from doses predicted by BSA scaling are common, as are large shifts in recommended doses at age thresholds. Further research is required to determine if better outcomes could be achieved by adopting biologically based scaling of paediatric doses.

Personalized medicine in inflammatory cardiomyopathy

Inflammatory cardiomyopathy is the result of persistent myocardial inflammation which can arise from both infectious or noninfectious causes. While most patients with acute myocarditis recover, up to 20% develop inflammatory cardiomyopathy with chronic heart failure. The interaction between host factors and factors of the agent that triggered myocardial inflammation must be considered to fully understand the individual mechanism of disease. Several inflammatory biomarkers, histology, immunohistochemistry, advanced imaging technologies as well as molecular high-throughput sequencing techniques help to identify disease pathways and to establish a comprehensive, individualized treatment approach, which can include anti-inflammatory medication, antiviral drugs and heart failure therapy. This might help to prevent transition from acute inflammation to persistent heart failure and to restore cardiac function.

Community Dissemination in a Tribal Health Setting: A Pharmacogenetics Case Study

Alaska Native and American Indian (AN/AI) people experience a disproportionate burden of health disparities in the United States. Including AN/AI people in pharmacogenetic research offers an avenue to address these health disparities, however the dissemination of pharmacogenetic research results in the community context can be a challenging task. In this paper, we describe a case-study that explores the preferences of AN/AI community members regarding pharmacogenetic research results dissemination. Results were presented as a PowerPoint presentation at the 2016 Alaska Native Health Research Forum (Forum). An audience response system and discussion groups were used to gather feedback from participants. Descriptive statistics were used to assess attendee understanding of the presentation content. Thematic analysis was used to analyze discussion group data. Forum attendees needed time to work through the concept of pharmacogenetics and looked for ways pharmacogenetics could apply to their daily life. Attendees found pharmacogenetics interesting, but wanted a simple description of pharmacogenetics. Community members were optimistic about the potential benefit pharmacogenetic medicine could have in the delivery of health care and expressed excitement this research was taking place. Researchers were urged to communicate throughout the study, not just end research results, to the community. Furthermore, attendees insisted their providers stay informed of research results that may have an impact on health care delivery. Conversational forms of dissemination are recommended when disseminating pharmacogenetic research results at the community level.

Parameter estimation for sigmoid Emax models in exposure-response relationship

The purpose of this simulation study is to explore the limitation of the population PK/PD analysis using data from a clinical study and to help to construct an appropriate PK/PD design that enable precise and unbiased estimation of both fixed and random PD parameters in PK/PD analysis under different doses and Hill coefficients. Seven escalating doses of virtual drugs with equal potency and efficacy but with five different Hill coefficients were used in simulations of single and multiple dose scenarios with dense sampling design. A total of 70 scenarios with 100 subjects were simulated and estimated 100 times applying 1-compartment PK model and sigmoid E_max model. The bias and precision of the parameter estimates in each scenario were assessed using relative bias and relative root mean square error. For the single dose scenarios, most PD parameters of sigmoid E_max model were accurately and precisely estimated when the C_max was more than 85% of EC₅₀, except for typical value and inter-individual variability of EC₅₀ which were poorly estimated at low Hill coefficients. For the multiple dose studies, the parameter estimation performance was not good. This simulation study demonstrated the effect of the relative range of sampled concentrations to EC₅₀ and sigmoidicity on the parameter estimation performance using dense sampling design.

MathIOmica: An Integrative Platform for Dynamic Omics

Multiple omics data are rapidly becoming available, necessitating the use of new methods to integrate different technologies and interpret the results arising from multimodal assaying. The MathIOmica package for Mathematica provides one of the first extensive introductions to the use of the Wolfram Language to tackle such problems in bioinformatics. The package particularly addresses the necessity to integrate multiple omics information arising from dynamic profiling in a personalized medicine approach. It provides multiple tools to facilitate bioinformatics analysis, including importing data, annotating datasets, tracking missing values, normalizing data, clustering and visualizing the classification of data, carrying out annotation and enumeration of ontology memberships and pathway analysis. We anticipate MathIOmica to not only help in the creation of new bioinformatics tools, but also in promoting interdisciplinary investigations, particularly from researchers in mathematical, physical science and engineering fields transitioning into genomics, bioinformatics and omics data integration.

Physiologically-based pharmacokinetic models: approaches for enabling personalized medicine

Personalized medicine strives to deliver the 'right drug at the right dose' by considering inter-person variability, one of the causes for therapeutic failure in specialized populations of patients. Physiologically-based pharmacokinetic (PBPK) modeling is a key tool in the advancement of personalized medicine to evaluate complex clinical scenarios, making use of physiological information as well as physicochemical data to simulate various physiological states to predict the distribution of pharmacokinetic responses. The increased dependency on PBPK models to address regulatory questions is aligned with the ability of PBPK models to minimize ethical and technical difficulties associated with pharmacokinetic and toxicology experiments for special patient populations. Subpopulation modeling can be achieved through an iterative and integrative approach using an adopt, adapt, develop, assess, amend, and deliver methodology. PBPK modeling has two valuable applications in personalized medicine: (1) determining the importance of certain subpopulations within a distribution of pharmacokinetic responses for a given drug formulation and (2) establishing the formulation design space needed to attain a targeted drug plasma concentration profile. This review article focuses on model development for physiological differences associated with sex (male vs. female), age (pediatric vs. young adults vs. elderly), disease state (healthy vs. unhealthy), and temporal variation (influence of biological rhythms), connecting them to drug product formulation development within the quality by design framework. Although PBPK modeling has come a long way, there is still a lengthy road before it can be fully accepted by pharmacologists, clinicians, and the broader industry.

Partnership with the Confederated Salish and Kootenai Tribes: Establishing an Advisory Committee for Pharmacogenetic Research

BACKGROUND

Inclusion of American Indian and Alaska Native (AI/AN) populations in pharmacogenetic research is key if the benefits of pharmacogenetic testing are to reach these communities. Community-based participatory research (CBPR) offers a model to engage these communities in pharmacogenetics.

OBJECTIVES

An academic-community partnership between the University of Montana (UM) and the Confederated Salish and Kootenai Tribes (CSKT) was established to engage the community as partners and advisors in pharmacogenetic research.

METHODS

A community advisory committee, the Community Pharmacogenetics Advisory Council (CPAC), was established to ensure community involvement in the research process. To promote bidirectional learning, researchers gave workshops and presentations about pharmacogenetic research to increase research capacity and CPAC members trained researchers in cultural competencies. As part of our commitment to a sustainable relationship, we conducted a self-assessment of the partnership, which included surveys and interviews with CPAC members and researchers.

RESULTS

Academic and community participants agree that the partnership has promoted a bidirectional exchange of knowledge. Interviews showed positive feedback from the perspectives of both the CPAC and researchers. CPAC members discussed their trust in and support of the partnership, as well as having learned more about research processes and pharmacogenetics. Researchers discussed their appreciation of CPAC involvement in the project and guidance the group provided in understanding the CSKT community and culture.

DISCUSSION

We have created an academic-community partnership to ensure CSKT community input and to share decision making about pharmacogenetic research. Our CBPR approach may be a model for engaging AI/AN people, and other underserved populations, in genetic research.

Skeletal Muscle Differentiation on a Chip Shows Human Donor Mesoangioblasts' Efficiency in Restoring Dystrophin in a Duchenne Muscular Dystrophy Model

: Restoration of the protein dystrophin on muscle membrane is the goal of many research lines aimed at curing Duchenne muscular dystrophy (DMD). Results of ongoing preclinical and clinical trials suggest that partial restoration of dystrophin might be sufficient to significantly reduce muscle damage. Different myogenic progenitors are candidates for cell therapy of muscular dystrophies, but only satellite cells and pericytes have already entered clinical experimentation. This study aimed to provide in vitro quantitative evidence of the ability of mesoangioblasts to restore dystrophin, in terms of protein accumulation and distribution, within myotubes derived from DMD patients, using a microengineered model. We designed an ad hoc experimental strategy to miniaturize on a chip the standard process of muscle regeneration independent of variables such as inflammation and fibrosis. It is based on the coculture, at different ratios, of human dystrophin-positive myogenic progenitors and dystrophin-negative myoblasts in a substrate with muscle-like physiological stiffness and cell micropatterns. Results showed that both healthy myoblasts and mesoangioblasts restored dystrophin expression in DMD myotubes. However, mesoangioblasts showed unexpected efficiency with respect to myoblasts in dystrophin production in terms of the amount of protein produced (40% vs. 15%) and length of the dystrophin membrane domain (210-240 µm vs. 40-70 µm). These results show that our microscaled in vitro model of human DMD skeletal muscle validated previous in vivo preclinical work and may be used to predict efficacy of new methods aimed at enhancing dystrophin accumulation and distribution before they are tested in vivo, reducing time, costs, and variability of clinical experimentation.

SIGNIFICANCE

This study aimed to provide in vitro quantitative evidence of the ability of human mesoangioblasts to restore dystrophin, in terms of protein accumulation and distribution, within myotubes derived from patients with Duchenne muscular dystrophy (DMD), using a microengineered model. An ad hoc experimental strategy was designed to miniaturize on a chip the standard process of muscle regeneration independent of variables such as inflammation and fibrosis. This microscaled in vitro model, which validated previous in vivo preclinical work, revealed that mesoangioblasts showed unexpected efficiency as compared with myoblasts in dystrophin production. Consequently, this model may be used to predict efficacy of new drugs or therapies aimed at enhancing dystrophin accumulation and distribution before they are tested in vivo.

Revisiting the Middle Molecule Hypothesis of Uremic Toxicity: A Systematic Review of Beta 2 Microglobulin Population Kinetics and Large Scale Modeling of Hemodialysis Trials In Silico

Background

Beta-2 Microglobulin (β2M) is a prototypical “middle molecule” uremic toxin that has been associated with a higher risk of death in hemodialysis patients. A quantitative description of the relative importance of factors determining β2M concentrations among patients with impaired kidney function is currently lacking.

Methods

Herein we undertook a systematic review of existing studies reporting patient level data concerning generation, elimination and distribution of β₂M in order to develop a population model of β₂M kinetics. We used this model and previously determined relationships between predialysis β₂M concentration and survival, to simulate the population distribution of predialysis β₂M and the associated relative risk (RR) of death in patients receiving conventional thrice-weekly hemodialysis with low flux (LF) and high flux (HF) dialyzers, short (SD) and long daily (LD) HF hemodialysis sessions and on-line hemodiafiltration at different levels of residual renal function (RRF).

Results

We identified 9 studies of 106 individuals and 156 evaluations of or more compartmental kinetic parameters of β₂M. These studies used a variety of experimental methods to determine β₂M kinetics ranging from isotopic dilution to profiling of intra/inter dialytic concentration changes. Most of the patients (74/106) were on dialysis with minimal RRF, thus facilitating the estimation of non-renal elimination kinetics of β₂M. In large scale (N = 10000) simulations of individuals drawn from the population of β₂M kinetic parameters, we found that, higher dialytic removal materially affects β₂M exposures only when RRF (renal clearance of β₂M) was below 2 ml/min. In patients initiating conventional HF hemodialysis, total loss of RRF was predicted to be associated with a RR of death of more than 20%. Hemodiafiltration and daily dialysis may decrease the high risk of death of anuric patients by 10% relative to conventional, thrice weekly HF dialysis. Only daily long sessions of hemodialysis consistently reduced mortality risk between 7–19% across the range of β₂M generation rate.

Conclusions

Preservation of RRF should be considered one of the therapeutic goals of hemodialysis practice. Randomized controlled trials of novel dialysis modalities may require large sample sizes to detect an effect on clinical outcomes even if they enroll anuric patients. The developed population model for β₂M may allow personalization of hemodialysis prescription and/or facilitate the design of such studies by identifying patients with higher β₂M generation rate.

A 30-years review on pharmacokinetics of antibiotics: is the right time for pharmacogenetics?

Drug bioavailability may vary greatly amongst individuals, affecting both efficacy and toxicity: in humans, genetic variations account for a relevant proportion of such variability. In the last decade the use of pharmacogenetics in clinical practice, as a tool to individualize treatment, has shown a different degree of diffusion in various clinical fields.

In the field of infectious diseases, several studies identified a great number of associations between host genetic polymor-phisms and responses to antiretroviral therapy. For example, in patients treated with abacavir the screening for HLA-B*5701 before starting treatment is routine clinical practice and standard of care for all patients; efavirenz plasma levels are influenced by single nucleotide polymorphism (SNP) CYP2B6-516G> T (rs3745274). Regarding antibiotics, many studies investigated drug transporters involved in antibiotic bioavailability, especially for fluoroquinolones, cephalosporins, and antituberculars. To date, few data are available about pharmacogenetics of recently developed antibiotics such as tigecycline, daptomycin or linezolid. Considering the effect of SNPs in gene coding for proteins involved in antibiotics bioavailability, few data have been published.

Increasing knowledge in the field of antibiotic pharmacogenetics could be useful to explain the high drug inter-patients variability and to individualize therapy. In this paper we reported an overview of pharmacokinetics, pharmacodynamics, and pharmacogenetics of antibiotics to underline the importance of an integrated approach in choosing the right dosage in clinical practice.

Pharmacogenetic research in partnership with American Indian and Alaska Native communities

Pharmacogenetics is a subset of personalized medicine that applies knowledge about genetic variation in gene-drug pairs to help guide optimal dosing. There is a lack of data, however, about pharmacogenetic variation in underserved populations. One strategy for increasing participation of underserved populations in pharmacogenetic research is to include communities in the research process. We have established academic-community partnerships with American Indian and Alaska Native people living in Alaska and Montana to study pharmacogenetics. Key features of the partnership include community oversight of the project, research objectives that address community health priorities, and bidirectional learning that builds capacity in both the community and the research team. Engaging the community as coresearchers can help build trust to advance pharmacogenetic research objectives.

Why the Shift? Taking a Closer Look at the Growing Interest in Niche Markets and Personalized Medicine

Pharmaceutical research and development is increasingly focused on niche markets, most notably treatments for rare diseases and “personalized” medicine. Drawing on the results of a qualitative study of 34 key Canadian stakeholders (including drug regulators, funders, scientists, policy experts, pharmaceutical industry representatives, and patient advocates), we explore the major trends that are reportedly contributing to the growing interest of the pharmaceutical industry in niche markets. Informed by both these key informant interviews and a review of the relevant literature, our paper provides a critical analysis of the many different—and sometimes conflicting—views on the reasons for and extent of the shift toward niche markets. We consider some of the potential advantages to industry, as well the important implications and risks that arise from the increasing pursuit of niche markets and pharmacogenomics. While there are many potential benefits associated with targeted therapies and drug development for historically neglected rare diseases, niche market therapies also present evidentiary challenges (e.g., smaller clinical trials and enrichment strategies) that can make approval decisions difficult, and uncertainties remain around the true benefits of many therapies.

On the Slow Diffusion of Point-of-Care Systems in Therapeutic Drug Monitoring

Recent advancements in point-of-care (PoC) technologies show great transformative promises for personalized preventative and predictive medicine. However, fields like therapeutic drug monitoring (TDM), that first allowed for personalized treatment of patients' disease, still lag behind in the widespread application of PoC devices for monitoring of patients. Surprisingly, very few applications in commonly monitored drugs, such as anti-epileptics, are paving the way for a PoC approach to patient therapy monitoring compared to other fields like intensive care cardiac markers monitoring, glycemic controls in diabetes, or bench-top hematological parameters analysis at the local drug store. Such delay in the development of portable fast clinically effective drug monitoring devices is in our opinion due more to an inertial drag on the pervasiveness of these new devices into the clinical field than a lack of technical capability. At the same time, some very promising technologies failed in the clinical practice for inadequate understanding of the outcome parameters necessary for a relevant technological breakthrough that has superior clinical performance. We hope, by over-viewing both TDM practice and its yet unmet needs and latest advancement in micro- and nanotechnology applications to PoC clinical devices, to help bridging the two communities, the one exploiting analytical technologies and the one mastering the most advanced techniques, into translating existing and forthcoming technologies in effective devices.

Defining 'elderly' in clinical practice guidelines for pharmacotherapy

OBJECTIVE

To identify how 'elderly' patients are defined and considered within Australian clinical guidelines for the use of pharmacotherapy.

METHOD

Guidelines pertaining to the use of pharmacotherapy, focusing on conditions described in National Health Priority Areas, were identified using databases (Medline, Google Scholar) and organisation websites (Department of Health and Ageing, National Heart Foundation, National Health and Medical Research Council). Guidelines were reviewed and qualitatively analysed to identify any references or definitions of 'elderly' persons.

RESULTS

Among the 20 guidelines reviewed, 3 defined 'elderly' by chronological age (i.e., years since birth) while the remaining 17 guidelines did not define 'elderly' in any way. All 20 guidelines used the term 'elderly', whilst some guidelines provided age (chronological)-based dosage recommendations suggesting an ageist or generalist approach in their representation of 'elderly', for which rationale was seldom provided. Thematic analysis of the statements revealed five key themes regarding how 'elderly' was considered within the guidelines, broadly describing 'elderly' persons as being frail and with altered pharmacology. Some guidelines also highlighted the limited evidence base to direct clinical decision-making. A continuum of perceptions of ageing also emerged out of the identified themes.

CONCLUSION

Clinical practice guidelines currently do not adequately define 'elderly' persons and provide limited guidance on how to apply treatment recommendations to older persons. The representation of 'elderly' in guidelines needs to be less based on chronological age or generic definitions focusing more on establishing a direct link between an individual patient's characteristics and the pharmacology of their prescribed medication. Clinical guidelines that do not offer any practical descriptions of the features of ageing that are specifically related to the use of pharmacotherapy, or how to assess these in individual patients, render decision-making challenging.

Computational pharmacology of rifampin in mice: an application to dose optimization with conflicting objectives in tuberculosis treatment

Dose selection for rifampin in the treatment of active pulmonary tuberculosis (TB) illustrates some of the challenges for dose optimization within multidrug therapies. Rifampin-based anti-TB regimens are often combined with antiretroviral therapies to treat human immunodeficiency virus (HIV) coinfection. The potent cytochrome P450 (CYP) enzyme inducing properties of rifampin give rise to significant drug-drug interactions, the minimization of which by limiting the dose, conflicts with the maximization of bacterial killing by increasing the dose. Such multiple and conflicting objectives lead to a set of trade-off optimal solutions for dose optimization rather than a single best solution. Here, we combine pharmacokinetic/pharmacodynamic (PK/PD) modeling with multiobjective optimization to quantitatively explore trade-offs between therapeutic and adverse effects of optimal dosing for the example of rifampin in TB-infected mice. The PK/PD model describes rifampin concentrations in plasma and liver following oral administration together with hepatic CYP enzyme induction and bacterial killing kinetics. We include optimization objectives descriptive of antimicrobial efficacy, CYP-mediated drug-drug interactions, and drug exposure-dependent toxicity. Results show non-conventional dosing scenarios that allow for increased efficacy relative to uniform dosing without increasing drug-drug interactions. Additionally, we find currently employed dosages for rifampin to be nearly optimal with respect to trade-offs between efficacy and toxicity. While limited by the accuracy and applicability of the PK/PD model, these results provide an avenue for experimental investigation of complex dose optimization problems. This method can be extended to include additional drugs and optimization objectives, and may provide a useful tool for individualized medicine.

Pharmacogenomics in early-phase clinical development

Pharmacogenomics (PGx) offers the promise of utilizing genetic fingerprints to predict individual responses to drugs in terms of safety, efficacy and pharmacokinetics. Early-phase clinical trial PGx applications can identify human genome variations that are meaningful to study design, selection of participants, allocation of resources and clinical research ethics. Results can inform later-phase study design and pipeline developmental decisions. Nevertheless, our review of the clinicaltrials.gov database demonstrates that PGx is rarely used by drug developers. Of the total 323 trials that included PGx as an outcome, 80% have been conducted by academic institutions after initial regulatory approval. Barriers for the application of PGx are discussed. We propose a framework for the role of PGx in early-phase drug development and recommend PGx be universally considered in study design, result interpretation and hypothesis generation for later-phase studies, but PGx results from underpowered studies should not be used by themselves to terminate drug-development programs.

Clopidogrel and warfarin pharmacogenetic tests: what is the evidence for use in clinical practice?

PURPOSE OF REVIEW

To review the most promising genetic markers associated with the variability in the safety or efficacy of warfarin and clopidogrel and highlight the verification and validation initiatives for translating clopidogrel and warfarin pharmacogenetic tests to clinical practice.

RECENT FINDINGS

Rapid advances in pharmacogenetics, continuous decrease in genotyping cost, development of point-of-care devices and the newly established clinical genotyping programs at several institutions hold the promise of individualizing clopidogrel and warfarin based on genotype. Guidelines have been established to assist clinicians in prescribing clopidogrel or warfarin dose based on genotype. However, the clinical utility of clopidogrel and warfarin is still limited. Accordingly, large randomized clinical trials are underway to define the role of clopidogrel and warfarin pharmacogenetics in clinical practice.

SUMMARY

Pharmacogenetics has offered compelling evidence toward the individualization of clopidogrel and warfarin therapies. The rapid advances in technology make the clinical implementation of clopidogrel and warfarin pharmacogenetics possible. The clinical genotyping programs and the ongoing clinical trials will help in overcoming some of the barriers facing the clinical implementation of clopidogrel and warfarin pharmacogenetics.

A taste of individualized medicine: physicians' reactions to automated genetic interpretations

The potential of pharmacogenomics is well documented, and functionality exploiting this knowledge is about to be introduced into electronic medical records. To explore physicians' reactions to automatic interpretations of genetic tests, we built a prototype with a simple interpretive algorithm. The algorithm was adapted to the needs of physicians handling immunosuppressive treatment during organ transplantation. Nine physicians were observed expressing their thoughts while using the prototype for two patient scenarios. The computer screen and audio were recorded, and the qualitative results triangulated with responses to a survey instrument. The physicians' reactions to the prototype were very positive; they clearly trusted the results and the theory behind them. The explanation of the algorithm was prominently placed in the user interface for transparency, although this design led to considerable confusion. Background information and references should be available, but considerably less prominent than the result and recommendation.

Plurigon: three dimensional visualization and classification of high-dimensionality data

High-dimensionality data is rapidly becoming the norm for biomedical sciences and many other analytical disciplines. Not only is the collection and processing time for such data becoming problematic, but it has become increasingly difficult to form a comprehensive appreciation of high-dimensionality data. Though data analysis methods for coping with multivariate data are well-documented in technical fields such as computer science, little effort is currently being expended to condense data vectors that exist beyond the realm of physical space into an easily interpretable and aesthetic form. To address this important need, we have developed Plurigon, a data visualization and classification tool for the integration of high-dimensionality visualization algorithms with a user-friendly, interactive graphical interface. Unlike existing data visualization methods, which are focused on an ensemble of data points, Plurigon places a strong emphasis upon the visualization of a single data point and its determining characteristics. Multivariate data vectors are represented in the form of a deformed sphere with a distinct topology of hills, valleys, plateaus, peaks, and crevices. The gestalt structure of the resultant Plurigon object generates an easily-appreciable model. User interaction with the Plurigon is extensive; zoom, rotation, axial and vector display, feature extraction, and anaglyph stereoscopy are currently supported. With Plurigon and its ability to analyze high-complexity data, we hope to see a unification of biomedical and computational sciences as well as practical applications in a wide array of scientific disciplines. Increased accessibility to the analysis of high-dimensionality data may increase the number of new discoveries and breakthroughs, ranging from drug screening to disease diagnosis to medical literature mining.

Can 'humanized' mice improve drug development in the 21st century?

Chimeric mice, which have human hepatocytes engrafted in their liver, have been used to study human drug metabolism and pharmacodynamic responses for nearly 20 years. However, there are very few examples where their use has prospectively impacted the development of a candidate medication. Here, three different chimeric mouse models and their utility for pharmacology studies are evaluated. Several recent studies indicate that using these chimeric mouse models could help to overcome traditional (predicting human-specific metabolites and toxicities) and 21st century problems (strategies for personalized medicine and selection of optimal combination therapies) in drug development. These examples suggest that there are many opportunities in which the use of chimeric mice could significantly improve the quality of preclinical drug assessment.

Personal genomes, quantitative dynamic omics and personalized medicine

The rapid technological developments following the Human Genome Project have made possible the availability of personalized genomes. As the focus now shifts from characterizing genomes to making personalized disease associations, in combination with the availability of other omics technologies, the next big push will be not only to obtain a personalized genome, but to quantitatively follow other omics. This will include transcriptomes, proteomes, metabolomes, antibodyomes, and new emerging technologies, enabling the profiling of thousands of molecular components in individuals. Furthermore, omics profiling performed longitudinally can probe the temporal patterns associated with both molecular changes and associated physiological health and disease states. Such data necessitates the development of computational methodology to not only handle and descriptively assess such data, but also construct quantitative biological models. Here we describe the availability of personal genomes and developing omics technologies that can be brought together for personalized implementations and how these novel integrated approaches may effectively provide a precise personalized medicine that focuses on not only characterization and treatment but ultimately the prevention of disease.