PK/PD

Clinical Pharmacokinetic Studies in Drug Development

2009-06-16T18:55:00.003-04:00

I wanted to compile a list of various PK studies conducted during the course of drug development. Several studies are conducted in the early phase of clinical development to understand the pharmacokinetics (PK) of a new drug in healthy human volunteers and/or patients. The objective of such PK studies is to evaluate the absorption, distribution, metabolism and excretion (ADME) of a new drug in humans.

Information gathered during these studies include PK parameters such as area under the curve (AUC, exposure), Cmax (maximum concentration) , Tmax (Time to Cmax), half life, clearance, volume of distribution, bioavailability, steady state plasma concentrations, accumulation ratio, linear or nonlinear PK, time dependent PK (auto-induction), plasma protein binding, metabolite identity and their PK.

Here goes the list.

1. Single Ascending Dose (SAD)
2. Multiple Ascending Dose (MAD)
3. Food Effect Studies
4. ADME Mass Balance Studies
5. Absolute/Relative Bioavailability
6. Thorough QTc Study
7. Drug Interaction Studies - Enzyme Inhibition/Induction
8. Effect of Age and Gender
9. Special Population - Hepatic Impairment
10. Special Populaiton - Renal Impairment
11. Impact of Genetic Polymorphisms of Drug Metabolizing Enzymes

I will be blogging on each of these topics in the next few weeks. I am quite keen to know how modeling & simulation approaches have been used in early clinical PK studies. Feel free to share your thoughts/comments, any unusual experiences in the conduct of these studies.

Phase 0 Microdosing/Microtracing in Phase 1 Studies

2009-06-09T20:33:00.007-04:00

Stephen Dueker, PhD, President/CEO of Vitalea Science recently commented on my previous post on Microdosing Studies. I thought of posting his comments and his email content pertaining to Microdosing/Microtracer studies in Phase 1 as a fresh post. Steve has also generously provided his recent presentation at ASMS meeting to be posted on this blog.

--------------------

All the methods and procedures for bioAMS were developed at Lawrence Livermore National Lab (LLNL) and the latest technology, the BioMICADAS developed by ETH/Zwitzerland and Vitalea Science (who has the original developer of bioAMS). It is important that people know the history of bioAMS and that it was the results of 15 years of intense research at Livermore in genotoxicity, nutrition, chemical interactions, pharmacology, and enviornmental studies. Other companies simply transferred some of the methods from LLNL.

What needs to be understood is that AMS is much more than Phase 0. As a CRO, many companies are doing microdosing as a means of "understanding the physiochemistry" of their compounds. The predictive PK topic is not the primary objective of microdosing, as PK can be solved later in formulation development. Microdosing is early ADME and understanding of the human metabolism. Receptor binding, tissue biopsies, cell loading, routes of elimination, protein binding, biotransformation, etc...can all be ascertained in a microdosing study. This indeed is what the specificity of a tracer and the sensitivity of AMS uncover.

There is a growing body of evidence that microdosing is predictive of macrodose PK, but again, that is not our (Vitalea's) principal focus nor would it be if I were a drug developer. Rank ordering multiple candidates is an interesting idea to supplant animal testing and I am surprised it is not used more, but generally developers are pretty attached to "their" candidate - thus we see scientists simply want to learn more so that they can have more efficient later Phase trials with fewer surprises. Analyses that we have been asked to do in microdosing proper are

Prodrug metabolism
Cellular penetration (Cell Loading)
Confirm absence or presence of unwanted metabolites
Potential for protein binding
Balance (does the drug come out).

I think this last point is important, as one will never see deep reservoirs with macrodose ADME clearly. We have seen drug material leak out for weeks in some cases for a 6 hr half-life drug. None of it is parent drug. When these drugs become daily doses, these reservoirs accumulate and essentially lead to self-drugging by the drug and its metabolites. The impact this could have on idiosyncratic adverse events and safety in general, is real, and should be known in advance. Macrodoses swamp the system and tell little of the PhysioKemistry that is alway active, but not perceptible.

It is everyone’s desire to find a panacea to the complexity of drug development. Perhaps that is unrealistic. I see a new age where companies spend more time on their molecules, understanding and viewing metabolism and PhysioKemistry not as a nuisance, but as a tool to understand the drug fully (or class of compounds) avoid the potential for later stage surprises, and streamline IND phase testing once it commences.

The marginal relevance of animal testing is clear despite the objections of the preclin crowd (no disrespect here) - how can sub-therapeutical human data not be valuable in myriad ways. That is the question to be asked? Not is microdosing predictive of macrodose PK. Pharmacokinetic prediction is great, but metabolism impacts safety in unexpected ways. Microdosing or Phase 1 ADME using microtracers is a very good option to make better decisions.The hot topic is now MIST guidance, not so much Phase 0. AMS finds all metabolites without method development or internal standards.

Just coming back from ASMS, it is clear that MIST guidance has put a good deal of "concern" into the pharma business about how to address this important safety issue of steady state metabolite exposure. While my head is still trying to sort through the myriad configurations of hybridized MS instrumentation, the common theme running through all the very excellent MS talks was that radioanalysis is the most straightforward and absolute means of addressing MIST. Non-traditional radioanalysis, using AMS, expedites the entire endeavor.

It would appear that the field has come full circle - nothing is so powerful as a near 0 background analysis (14C) for unequivocal metabolite discovery, After discovery, one would then need to enlist the many sophisticated and quite impressive MS techniques for metaID when odd metabolites are revealed.

I do not see PK as the most important issue. Safety and Efficacy are the issue, and PhysioKemistry provides a view into processes that impact the later. This is a complex business. I am not sure if "more shots on goal" by emphasizing speed over understanding is the way to go.

Steve

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Feel free to discuss and share your experience with Microdosing/AMS/Microtracer studies.

Clinical Pharmacology

2009-04-30T08:11:00.002-04:00

Its been a while since I had posted anything here. While I have been busy juggling between being a dad to a month old boy and trying to finish thesis work, I try to find time to recap and update myself on PK/PD. Here is a link with lots of presentations on various concepts of clinical pharmacology by authors of the book "Principles of Clinical Pharmacology".

http://www.cc.nih.gov/training/training/principles/schedule.html

Have fun learning!

PKPD Regulatory Guidances

2008-12-15T15:49:00.011-05:00

After a short hiatus, I am back and hope to continue posting frequently. Ok. If you are planning to work in the industry or already dealing with population PK studies, then you may want to read the guidances pertaining to PK/PD. These guidances provide recommendations on study design, data analysis and report writing which can be very helpful in your work.

Listed below are some guidances where PopPK or PK/PD studies are recommended by FDA or EMEA.

Population Pharmacokinetics [PDF] - This document provides recommendation on the study design and execution, model development & validation and reporting the results of a PopPK analysis. Some examples of how the results are used in drug labeling are also provided. However, the document doesnt delve deep into the qualification of softwares used for such analysis. Neither does it talk about any preferred softwares like NONMEM or SAS or Splus.

Guideline on Reporting the Results of Population Pharmacokinetic Analysis [PDF] - This EMEA guideline provides in detail the information required in a report submitted for their review. I like this document over FDA's guidance especially because they spell out exactly the kind of information one needs to report in terms of NONMEM lingo eg, choice of analysis (parametric or non parametric or bayesian), estimation methods (FO vs FOCE vs FOCE INTER), GOF plots like DV vs PRED, DV vs IPRED (with line of identity and trend line (:>)) and so forth.

Other guidances that recommend PK/PD evaluations include

FDA Final Guidance on exposure-response relationships - study design, data analysis and regulatory applications. [PDF]
Pharmacokinetics in Pregnancy— Study Design, Data Analysis, and Impact on Dosing and Labeling [PDF] -
Guideline on the Role of Pharmacokinetics in the Development of Medicinal Products in the Paediatric Population [PDF] - Efficay and safety data from adults can be extrapolated to obtain PK information for paediatric patients. When PK studies are to be carried out in paediatric population, PopPK studies with sparse sampling methodolgy seems to be the best approach. In young patients, there is rapid maturation of organs that are involved in drug absorption, distribution and elimination necessiating different dosage regimen. Thus for drugs that are intended to be used in paediatrics, this document provides recommendations on the study design of PK studies.

AAPS Annual Meeting

2008-11-14T10:43:00.004-05:00

I will be in Atlanta for AAPS meeting between 15-20 Nov. I would be happy to meet you, if you are planning to attend. Let me know via comments or by emailing me at ganesh.mugundu [at]gmail.com.

NONMEM Resources

2008-11-03T19:56:00.008-05:00

I started learning NONMEM through a local discussion group headed by Dr. Alexander A. Vinks, at Cincinnati Childrens hospital. The small group comprised of few MS/PhD graduate students (including me) and faculty from pharmacy/mathematics. We have been meeting biweekly since 2006 and discuss about modeling data using NONMEM and other statistical softwares. Each of us had an opportunity to use real clinical data obtained from paediatric patients and develop PK/PD models to describe the data. We had guest lectures by Nick Holford MD, Dr. Roger Jeliffe MD, Jurgen Bulitta PhD about the use of NONMEM, USC Pack in population PK/PD modeling. Modeling and simulation has now become an integral part of drug development process and is being used regularly to model preclinical/clinical data.

Ok. My main objective of this post was to share some resources that are available to learn model data using NONMEM. In addition to the above discussion group, I have learnt immensely from the following resources.

a. Resources by Nick Holford: These course materials are freely available with enough background information to start performing population PKPD analysis.

b.Resource Facility for Population Pharmacokinetics[RFPK] – When accessing this site, you will have to fill a short questionnaire before downloading or viewing the tutorials/ presentations.

c. Nonlinear mixed effect models: an overview and update [PDF]

d. Laboratory of Applied Pharmacokinetics (LAPK) teaching resources by Roger Jeliffe.

New Advances in PK/PD Modeling [PDF]
Pop PK: Parametric & Non parametric Approaches [PDF]
Bayes Theorem and Other PK resources [PDF]

e. Pharmacometrics by ACCP

f. Regulatory Guidances

US FDA Population Pharmacokinetics [PDF]
EMEA Guideline on Reporting the Results of Population Pharmacokinetic Analyses [PDF]

If you know of more resources that can be added to this list, please feel free to provide the information by way of comments. Good night!

Data Presentation

2008-11-01T11:57:00.007-04:00

Here is an excellent video on data presentation by Hans Rosling.

Let me know your thoughts if you enjoyed this video!

Good Modeling

2008-10-29T17:46:00.003-04:00

Here is something to think about...

From a mathematical point of view, the art of good modeling relies on: (i) a sound understanding and appreciation of the biological problem; (ii) a realistic mathematical representation of the important biological phenomena; (iii) finding useful solutions, preferably quantitative; and most crucially important, (iv) a biological interpretation of the mathematical results in terms of insights and predictions. The mathematics is dictated by the biology and not vice versa. Sometimes the mathematics can be very simple. Useful mathematical biology research is not judged by mathematical standards but by different and no less demanding ones.

- Jim Murray, 1993

Hepatotoxicity in Drug Development

2008-10-25T15:42:00.003-04:00

Liver toxicity has been one of the most common reasons for drug withdrawal in the past e.g Benoxaprofen (Oraflex), ticrynafen (Selacryn), bromfenac (Duract) and troglitizone (Rezulin). It has lead to black box warning for drugs like rifampicin, acetaminophen, valproic acid etc, due to their potential to cause liver injury. In some cases, drugs have not been approved because of its hepatotoxicity. Acetaminophen is a classic example where drug induced liver injury (DILI) is observed due to overdosage. The mechanism involves formation of a highly reactive metabolite N-Acetyl-p-benzoquinoneimine, by cytochrome P450 enzymes (CYPs) CYP2E1, CYP1A2, and CYP3A4. Accumulation of this metabolite results in cell death and hepatocellular necrosis. Patients with acetaminophen hepatotoxicity are treated with N-acetylcysteine, but still approximately 500 patients die each year.

In the course of drug discovery and development, why is it difficult to determine the potential of a new chemical entity to cause hepatotoxicity or DILI? Though every compound undergoes rigorous testing in animal models and in vitro hepatocytes, most of the compounds pass through without being identified as hepatotoxic, probably due to lack of an appropriate model or due to differences in absorption, distribution, metabolism, elimination (ADME) between humans & animals. Other reasons include age, sex, genetic polymorphisms, disease conditions, drug -food and drug-drug interactions (CYP Induction/Inhibition). All these factors decrease the predictive power of non-clinical studies.

An increase in levels of the liver enzymes like alanine aminotransferase (ALT) and aspartate aminotransferase (AST), alkaline phosphatase (ALP) and total bilirubin are signs of liver toxicity. Evaluation of these enzymes are routinely performed in clinical trials to assess drug induced liver injury. According to FDA guidance document, Hy’s Law (Hy Zimmerman) in determining DILI cases have the following three components:

“1. The drug causes hepatocellular injury, generally shown by more frequent 3-fold or greater elevations above the ULN of ALT or AST than the (nonhepatotoxic) control agent or placebo.
2. Among subjects showing such aminotransferase (AT) elevations, often with ATs much greater than 3xULN, some subjects also show elevation of serum TBL to >2xULN, without initial findings of cholestasis (serum alkaline phosphatase (ALP) activity >2xULN).
3. No other reason can be found to explain the combination of increased AT and TBL, such as viral hepatitis A, B, or C, preexisting or acute liver disease, or another drug capable of causing the observed injury.”

If a patient has found to have AT 3xULN or TBL is greater than 2xULN, the tests need to be repeated within 48-72 hours to confirm the abnormalities.

A recent example of hepatotoxicity observed in a new drug and the response of FDA has been cited in a white paper formulated for the workshop “Assessing and Accelerating Development of Biomarkers for Drug Safety” as follows

“A major pharmaceutical company submitted an NDA application for treatment of a chronic disease. The FDA agreed with the sponsor’s efficacy data. However, it was noted that among ~4,000 treated patients in clinical trials, two developed elevations in both serum alanine aminotransferase and bilirubin. As a prerequisite for approval, the company was told to conduct a new safety study of 10,000 patients treated with drug for one year, and to also include an additional 10,000 subjects receiving comparator treatment for one year. This news will cost the company >$200M to conduct the trial, ~3 years off patent, and loss of market entry position in class.”

This clearly shows how important it is to determine the toxicity to liver during the phases of drug development. I guess this post will stimulate some fruitful discussions and ideas related to DILI.

Other Guidances/References: EMEA -Non-Clinical Guideline On Drug-Induced Hepatotoxicity[PDF], FDA White Paper on Nonclinical Assessment of Potential Hepatotoxicity in Man [PDF]

Please feel free to share this post on technocrati , del.ici.ous and digg.

A=X+Y+Z: Sucess Formula

2008-10-23T07:22:00.005-04:00

Good Morning!

Here is something simple to think about-

"If A equal success, then the formula is A equals X plus Y and Z, with X being work, Y play, and Z keeping your mouth shut - Albert Einstein

Wish you "A" in your day!

MWSUG - Midwest SAS User Group Scholar

2008-10-20T23:16:00.009-04:00

I was fortunate enough to be selected as a student scholar in the recent midwest SAS user group conference held at Mariott Hotel, Indianapolis. This scholarship included a free registration and accomodation during the conference. It was a unique opportunity to mingle with SAS/JMP users from industry & academia and lean from the experts. The presentations were in the following categories

Application Development
Data Visualization
Pharmaceutical Applications
SAS Presents
Statistics and Data Analysis
Tutorials
JMP

Being a midwest user's conference, I think MWSUG 2008 had around 400-500 attendees and was a small one when compared to AAPS with approximately 10,000 attendees. Dr. John Sall, Co-founder and Executive Vice President of SAS Institute and leader of the JMP business division was the key note speaker. He talked about the journey of JMP since late 1980s to the current version of JMP7.0. I especially enjoyed the talk on Mixed Effect Models and Bayesian analysis using SAS. I am not a SAS/JMP expert, but am comfortable using them for some of the statistical analysis.

In addition to the various presentations and hands on SAS workshop, MWSUG included a Las Vegas Casino Night with games like Craps, Blackjack, Roulette, 3-Card Poker, Money Wheel and Texas Hold’em Poker area. Each of us received a $500 fake money to play the games. This was the second time I was ever gambling in my life (can you believe that?) and in a Mariott turned Las Vegas Casino. The first time was when I visited Las Vegas and was trying my hand at the slot machines. Anyways, I did have fun on the casino night.

Did you have an experience similar to this? I would be happy to hear and learn from you!

Population Pharmacokinetics/Pharmacodynamics

2008-10-18T22:28:00.002-04:00

Population pharmacokinetics (PopPk) is the study of variability in plasma concentrations between and within individuals. It helps in identifying the demographic, pathophysiological, environmental and drug related factors that contribute to the variability observed in safety and efficacy of a drug. Unlike traditional PK studies where healthy volunteers are subjected to intensive sampling to determine PK parameters, PopPk studies offer an advantage of estimating PK parameters in target patient population with sparse sampling methodology. PopPK uses a nonlinear mixed effects modeling (NONMEM) approach. Variability in NONMEM is characterized in terms of fixed and random effects. The fixed effects are population average values of pharmacokinetic parameters such as clearance & volume of distribution, that may in turn be a function of patient characteristics. The random effects quantify the variability that is not explained by the fixed effects. These random effects include inter-subject, intra-subject, inter-occasion and residual variability. This methodology has also been extended to model population pharmacokinetic/pharmacodynamics (Pop PK/PD) relationships. This NONMEM approach was introduced by Lewis Sheiner and Stuart Beal approximately 30 years back. It has now become an integral part of drug development in industries and FDA review process.

Some of the softwares that have been used for modeling are as follows
NONMEM (most widely used)
ADAPT
Monolix
NPEM
NPAG (USC*PACK)
WinNonmix
Kinetica
SAS (PROC NLMIXED)
Splus

Pop PK/PD has led to a new discipline known as pharmacometrics. Barrett et al in J Clin Pharmacol 2008;48:632-649 define “Pharmacometrics” as that branch of science concerned with mathematical models of biology, pharmacology, disease, and physiology used to describe and quantify interactions between xenobiotics and patients, including beneficial effects and side effects resultant from such interfaces. So if you are a pharmacist, pharmacologist, statistician or biomedical engineer with good understanding of pharmacokinetics, pharmacodynamics, biological sciences, statistical and computational tools, you have a good chance to become a pharmacometrician. They are paid well both in the industry and the FDA. Infact, FDA has its own pharmacometrics group headed by Joga Gobburu and are promoting the use of modeling & simulation in drug development.

Are you a pharmacometrician or a PK/PD scientist? Is there a specific software that you use to model the data?

Bioavailability/Bioequivalence Guidelines

2008-10-07T22:21:00.009-04:00

Sometimes its hard to find regulatory guidance documents on the web. One has to scroll through several pages before you actually find what you need. To make things easier, I previously had a webpage where the Bioavailability/Bioequivalence (BA/BE) guidances of various countries were put together under one page. Now, I will be posting the guidance documents on various topics on this blog. Today, I will start with BA/BE and cover as many topics in clincal pharmacology as possible in the future. If you are working in the generics industry and happen to do clinical studies supporting the ANDA (Abbreviated New Drug Application), you may want to bookmark this page and become familiar with following documents.

US FDA

1. Bioavailability and Bioequivalence Studies for Orally Administered Drug Products - General Considerations (Issued 3/2003, Posted 3/19/2003)[PDF]

2. Bioavailability and Bioequivalence Studies for Nasal Aerosols and Nasal Sprays for Local Action (Posted 4/2/2003)[PDF]
3. Waiver of In Vivo Bioavailability and Bioequivalence Studies for Immediate-Release Solid Oral Dosage Forms Based on a Biopharmaceutics Classification System (Issued 8/2000, Posted 8/31/2000) [PDF]
4. Food-Effect Bioavailability and Fed Bioequivalence Studies (Issued 12/2002, Posted 1/30/2003) [PDF]
5. Handling and Retention of BA and BE Testing Samples (5/25/2004) [PDF]
6. Statistical Approaches to Establishing Bioequivalence (Issued 2/2001, Posted 2/1/2001)[PDF]
7. Submission of Summary Bioequivalence Data for ANDAs (04/2009) [PDF]
8. Individual Product Bioequivalence Recommendations
9. Bioanalytical Method Validation [PDF]

Note: All links updated

EMEA

1. Guideline on the Investigation of Bioequivalence (July 2008)[PDF]

2. Guidance on the Investigation of Bioavailability and Bioequivalence (July 2001) [PDF]

3. Questions & Answers on the Bioavailabilty and Bioequivalence Guideline (July 2006) [PDF]

4. Reflection Paper on Advice to Applicants/Sponsors/CROs of Bioequivalence Studies (Oct 2007) [PDF]

5. Guidance on Validation of Analytical Procedures: Text and Methodology (June 1995) [PDF]

6. Concept Paper on BCS-Based Biowaiver (May 2007) [PDF]

7. Guidance on Modified Release Oral and Transdermal Dosage Forms(July 1999) [PDF]

CANADA (HPMB)

Bioavailability and Bioequivalence [html]

AUSTRALIA (TGA)
Guidance on the Investigation of Bioavailabiliy and Bioequivalence [PDF]

Helmut Schütz also maintains a comprehensive list of BABE guidelines of almost all the countries and you can find it here.

Let me know if I am missing something or if this information is helful to you!

A cup of Tea

2008-10-03T22:45:00.003-04:00

One of my favorite Zen story - A cup of Tea

Nan-in, a Japanese master during the Meiji era (1868-1912), received a university professor who came to inquire about Zen.

Nan-in served tea. He poured his visitor's cup full, and then kept on pouring.

The professor watched the overflow until he no longer could restrain himself. "It is overfull. No more will go in!"

"Like this cup," Nan-in said, "you are full of your own opinions and speculations. How can I show you Zen unless you first empty your cup?"

What do you think?

Clinical Pharmacology & Translational Research

2008-07-14T21:01:00.008-04:00

This year AAPS is hosting the national symposium at Atlanta, Georgia between November 16-20. I usually attend most of the presentations beginning from the sunrise session to the last one in the evening. The CPTR (Clinical Pharmacology & Translational Research) section has some very interesting sessions covering pharmacogenetics, modeling & simulation, biomarkers, pharmacokinetic models, drug metabolism & transport and is truly translational. Here is the list of CPTR sessions.

Sunday, November 16, 8:30 am – 4:00 pm
Short Course #5: Pharmacodynamic Modeling of Non-standard Endpoints

Tuesday, November 18, 7:00 am – 8:15 am
Clinical Applications of Pharmacogenetics Sunrise Session

Tuesday, November 18, 8:30 am – 11:00 am
Diabetes Disease Progression Modeling Symposium

2:00 pm – 4:00 pm
Quantitative Clinical Pharmacology Analyses: Communicating to Influence Decisions Roundtable

2:00 pm – 4:30 pm AAPS/ACCP Joint Symposium:
Success Achieved and Challenges Ahead in Translating Biomarkers into Clinical Applications

Why Absorption and Pharmacokinetic Models Are More Important in Future Drug Development Symposium

7:00 pm – 9:30 pm Controversies in PK/PD Model Development Open Forum

Wednesday, November 19 8:30 am – 11:00 am
Modeling and Simulation Strategies for Evaluation of Drug Safety in Clinical Studies

Symposium 2:00 pm – 4:00 pm
The Impact of Kidney Disease/Renal Impairment on Drug Metabolism and Transport Roundtable

I bet it's gonna be a good learning experience listening to leading experts in the field talk on these topics. What do you think? Will you be coming to AAPS this year? Do you have a poster/podium presentation? Are you an invited speaker? Apart from all the scientific talks, AAPS is a good place to meet friends, previous colleagues and provides ample opportunity for networking.

I hope to see you at AAPS meeting in Georgia. Take care!

First in Human Dose Calculation

2008-05-05T22:08:00.009-04:00

The other day, I got an opportunity to teach students of MS in Drug Development course about procedures used in calculating first human dose for Phase I clinical trials. I started out explaining the objectives of Phase I studies, various study designs and the need to estimate safe starting doses. The process outlined in the FDA guidance document for estimating the MRSD (Maximum Recommended Starting Dose) is based on doses administerd to different animal species, observed toxicities and a proposed algorithm (as mentioned below) . Additional methods reported include PK guided approach based on AUC and clearance. You can find my slides here.

Let me know your thoughts on these methods. All comments, suggestions, criticism will be highly appreciated.

PK Model (NONMEM)

2008-05-04T20:33:00.007-04:00

I have been working on a drug administerd orally to paediatric patient and follows a one compartmental model. Following is the control stream and the output obtained running the model with NONMEM VI. The estimates obtained do match the reported literature values. My next plan is to use the estimates obtained to model the PD data.

$PROB RUN# 100

$INPUT C ID TIME DV AMT DOSE MDV WT

$DATA 100.CSV IGNORE=C

$SUBROUTINES ADVAN2 TRANS2

$PK

TVCL=THETA(1)*(WT/70)**0.75

CL=TVCL*EXP(ETA(1))

TVV=THETA(2)*(WT/70)**1

V=TVV*EXP(ETA(2))

TVKA=THETA(3)

KA=TVKA*EXP(ETA(3))

S2=V
TAD=TIME SID=ID

$ERROR Y = F + F*ERR(1) + ERR(2)

IPRED=F

$EST METHOD=1 PRINT=20 NOABORT MAXEVAL=9999 MSFO=100.msf

$THETA

(0.1, 14) ;[CL/F]

(0.1, 51);[V]

(0.1, 8) ;[KA]

$OMEGA

0.09 ;[P] omega(1,1)

0.04 ;[P] omega(2,2)

0.36 ;[P] omega(3,3)

$SIGMA

0.09 ;[P] sigma(1,1)

0.1 ;[A] sigma(2,2)

$COVARIANCE
$TABLE ID SID TIME DV PRED IPRED CL V KA WT ONEHEADER NOPRINT FILE=100.tab
$$TABLE ID TIME IPRED WRES NOPRINT ONEHEADER FILE=SDTAB100

Output:

CL: 14.14 (37.7%), V:55.2 (20.7%), Ka: 8.12 (130%)

Residual Varaiability: Proportaional (15.4%), Additive (1.03 ug/ml)

Plots of few patients

Any comments/criticism/suggestions to improve the fit?

Learn Vs Confirm

2008-04-29T18:24:00.005-04:00

I was reading this interesting and thought provoking article on "LEARNING VS. CONFIRMING IN CLINICAL DRUG DEVELOPMENT" by Lewis Sheiner. The article is available freely on the web here. For those who havent read it, please do so. It may be hard to grasp the details in the first attempt, but if you read it more than once (like I am doing) you will start understanding how one can improve clinical drug development program by implementing the learn- confirm paradigm.

PK/PD Models

2008-04-29T17:40:00.006-04:00

All Models Are Wrong,

Some Models Are Useful. George Box

How does one find the useful model? Is the useful model the right one? Since the model keeps on changing with new information, I guess there can never be a right model.

Human Microdosing Studies/ Phase Zero

2008-04-25T12:25:00.018-04:00

A Phase Zer0 study involves evaluating pharmacokinetics of a drug after administration of sub-therapeutic or sub pharmacology doses to a small group of healthy volunteers. According to

EMEA position paper, microdose is defined as dose less than 1/100th of the dose calculated to yield a pharmacological effect or a maximum of <= to 100 mcg dose. Using such small doses pharmacokinetic parameters can be estimated using highly sensitive techniques like acceleratoor mass spectrometry (AMS) or positron emission tomography (PET).

Determining pharmacokinetics, pharmacodynamics (binding to target) and metabolism of a drug at such an early stage in humans will help in eliminating compounds that have suboptimal properties and can aid in go or no decision of a compound. This is believed to considerably reduce the cost and time of drug development. US FDA followed with Exploratory IND guidance document in 2006 for conducting such early phase clinical trials. Microdosing or phase 0 studies do not provide any information on safety and efficacy (because of subtherapeutic dose used).

Xceleron has been the forefront in microdosing studies and their site provides some valuable information for anyone interested. National cancer institute had organised a conference on Phase 0 in oncology drug development and am still going through the slides posted here. As such, there have been very few publications on the use of this strategy in drug development. A pubmed search revealed few publications listed below, though none of them are real drug development case studies.

So here is my question for you. Were you (or your company) involved in any mircodosing studies? What is your opinion on the long term use of Phase o studies? Can modeling & simulation play any role in extrapolating data from these studies?

Microdosing Study Publications
1. Clinical Cancer Research 13, 4164-4169, July 15, 2007
2. Clin Pharmacol Ther. 2006 Sep;80(3):203-15
3. Clin Pharmacol Ther. 2006 Sep;80(3):216-27
4. J Clin Pharmacol. 2005 Oct;45(10):1198-205

Do schools kill creativity?

2008-04-22T21:07:00.000-04:00

Check out this video...
http://www.ted.com/talks/view/id/66
I bet you would love this.

PKPD Books

2008-04-22T19:59:00.001-04:00

I havent had a chance to blog about anything in the past few days. I wanted to break the ice and start writing something today. So, here I go with the list of important books that I have read or am reading and am aiming to finish reading in the next few months. I usually start with the chapters most interesting and try to read a chapter a day. So here is my list...

1. Pharmacokinetic-Pharmacodynamics Modeling and Simulation -Peter L Bonate. I have already finished most chapters and feel its a very good book for beginners, loaded with all the essential basics, and boosting inspirational quotes at the start of each chapter.

2. Pharmacometrics: The Science of Quantitative Pharmacology - Ene I. Ette and Paul J. Williams. I have read the book and have used some of the NONMEM codes for parent metabolite, eneterohepatic recirculation and PKPD modeling. Excellent book and a must read for those aspiring to be a pharmacometrician.

3. Principles of Clinical Pharmacology. Arthur J. Atkinson et al. A very good book covering all aspects of clinical pharmacology with chapters on clinical pharmacogenetics, population pharmacokinetics, disease progression models, drug therapy in pregnant and nursing women, drug discovery and development... Very ineteresting range of topics and a must read.

4. Dose Optimization in Drug Development - Rajesh Krishna. As the title goes, this book provides views of various experts on dose selection and optimization in drug development. It covers important topics like disease progression modeling, dose selection in first in man studies, biomarkers, PK/PD variability, pharmacogenetics, paediatric dose optimization
As quoted by Rajesk Krishna " The book will appeal to anyone who would like to appreciate how integration of sciences facilitates meaningful changes in delineating risk versus benefit and ultimately in the selection of safe and effective doses"

How about you? I would appreciate if you could share some of the books that you have enjoyed learning.

Sex and/or Gender

2008-04-10T00:07:00.001-04:00

I was surprised to know that gender and sex have different meanings. During a presentation at Cincinnati Childrens Hospital, Dr. Nick Holford had asked us to explain the differences between sex and gender. There was a moment of silence amongst the students contemplating on the issue. It seems that the scientific community has been using the terms interchangeably. Sex based differences in pharmacokinetics of drugs have been investigated and there is a fair amount of literature suggesting men and women absorb, distribute and metabolise some drugs differently.

Women have been found to have higher gastric PH, slower gastric emptying rate, higher percentage of fat leading to higher volume of distribution, higher rates of metabolism for CYP3A4 substrates and higher rates of clearance for P-gp substrates. In addition, fluctuation in homonal levels have also been implicated for differences in CYP3A4 activity. However, there is a relative paucity of data on sex differences in pharmacodynamics of drugs. Perhaps the most dramatic example is women developing torsades de pointes (a type of ventricular arrythmia) after taking ceratin medications. Women treated with anti-HIV drugs, especially protease inhibtors have also had higher incidences of adverse effects in several studies. They also experienced greater efficacy rates when compared to men, emphasising the need of more prospective studies to identify the mechanisms behind these observations.

As the participation and inclusion of women in clinical trials increases, we will be able to understand the significance of these differences. Going back to the differences in the terminology of SEX and GENDER, Kim & Nafziger in their commentary (reference 1) state that gender and sex are distinct concepts. Sex differences between men and women are attributed to biologocal differences including genetic, hormonal, reproductive and physical differences. While, gender difference are attributed to behavioral and cultural aspects like smoking, alcohol consumption etc. More interesting points on the differences with examples at WHO site

Feel free to comment and correct!

References:
1. Is it sex or is it gender? Clin Pharmacol Ther 2000;68:1-3.
2. Sex differences in pharmacokinetics and pharmacodynamics. Annu Rev Pharmacol Toxicol. 2004;44:499-523.
3. The influence of sex on pharmacokinetics. Clin Pharmacokinet. 2003;42(2):107-21

I'm Blogging

2008-04-09T23:47:00.000-04:00

I have initiated this blog to enhance my understanding, and stimulate discussions on PK/PD principles & their use in drug development process . I would like to jump start my discussions by picking up some important manuscripts. Please feel free to comment, criticise and offer suggestions.