FDA Commissioner Scott Gottlieb on Quantitative Methods in Drug Development

Watch Gottlieb's speech where he outlines the steps FDA is taking to modernize how clinical information to make decisions about the safety/effectiveness of new drugs is being collected and evaluated. In particular he focuses on two aspects -

• Adaptive and seamless clinical trial approaches
• Better use of more advanced computing tools, and more sophisticated statistical and computational methodologies, as part of the drug development and the drug review process

Here is the transcript and a key message.

"In silico clinical trials use computer models and simulations to develop and evaluate devices and drugs. Modeling and simulation play a critical role in organizing diverse data sets and exploring alternate study designs. This enables safe and effective new therapeutics to advance more efficiently through the different stages of clinical trials. FDA’s efforts in modeling and simulation are enabled through multiple collaborations with external parties that provide additional expertise and infrastructure to advance the development of these state-of-the-art technologies.

FDA’s Center for Drug Evaluation and Research (CDER) is currently using modeling and simulation to predict clinical outcomes, inform clinical trial designs, support evidence of effectiveness, optimize dosing, predict product safety, and evaluate potential adverse event mechanisms. We’ll be putting out additional, updated guidance on how aspects of these in silico tools can be advanced and incorporated into different aspects of drug development."

My philosophy for a happy life | Sam Berns | TEDxMidAtlantic

We need better drugs--now

A very nice talk by Francis Collins.

Benefits of using modeling and simulation in drug development

Check out this video...a very nice illustration of how clinical pharmacologists use PKPD to influence decision making during drug development.

Cancer Drug Costs

 Interesting read on a review of cancer drug costs by ASCO.

Cost of Developing a New Drug

Oncology and Dose Finding

Earlier this year, US FDA and AACR  cosponsored a public workshop titled “Dose-finding of Small Molecule Oncology Drugs.” There were several interesting presentations and recommendations on how we can optimize the dose and dosing schedule during development. As in other therapeutic . areas, dose finding studies are usually not conducted during oncology drug development and the dose for phase 2/3 studies is typically based on MTD and PKPD data from limited patients in the dose escalation trial.


The goal was to promote a movement away from conventional dose escalation trial design and move toward innovative designs that can incorporate key clinical, pharmacologic, pharmacometric data, and when appropriate, non-clinical information to guide dose selection.

Check out the agenda, slides and recorded presentation at Dose-finding of Small Molecule Oncology Drugs

Bioavailability/Bioequivalence Regulatory Guidance Documents- Link Updated

After a long time, I have gone back and updated the guidance documents in my original post "Bioavailability/Bioequivalence Guidelines". There have been quite a number of changes to the documents, some have been revised and some have been replaced with new guidance documents. Let me know if I am missing something or if you find any broken links!.

Pharmacometric Tutorials

Some additional tutorials for learning population PK modeling and simulation have been published by  CPT: Pharmacometrics & Systems Pharmacology and are available for free under open access.

1. Basic Concepts in Population Modeling, Simulation, and Model-Based Drug Development
2. Basic Concepts in Population Modeling, Simulation, and Model-Based Drug Development—Part 2: Introduction to Pharmacokinetic Modeling Methods
3. A Time to Event Tutorial for Pharmacometricians
4. Establishing Best Practices and Guidance in Population Modeling: An Experience With an Internal Population Pharmacokinetic Analysis Guidance

Metrum Institute recently announced that their youtube videos on PK/PD training courses will be freely available to the public. This is an excellent news and kudos to them for making it available free of cost.  Something to bookmark and check out if you are interested to learn modeling and cant afford the training courses,

Video recordings and lecture notes from six semester-long courses (MI205,
MI210, MI212, MI250, MI255, and MI260) can be found on the Metrum Institute
YouTube channel (http://www.youtube.com/metruminst). Topics include: R
programming for pharmacometrics, introductory and intermediate topics in
population PK modeling, modeling continuous and categorical population PKPD
data, Bayesian PKPD modeling, and Bayesian model-based meta-analysis.

Happy Holidays!

The Role of Clinical Pharmacology in the Trial of Conrad Murray

One of the key  highlights of ASCPT 2013 was the presentation by Dr. Shafer on "The Role of Clinical Pharmacology in the Trial of Conrad Murray". If you have not seen his presentation, I would strongly encourage you to do so.  Dr. Shafer does an excellent job in explaining the concepts of PK, PD, simulations  and pharmacometrics in simple words to the jurors. This is a practical example of the utility of PK/PD modeling & simulation. So, sit back and enjoy the presentation.

Clinical Pharmacokinetic Studies in Drug Development

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

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.

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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

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

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.

More in my next post...

AAPS Annual Meeting

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

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.

1. Pharmacometrics
2. Advanced Pharmacometrics

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.

1. Tutorials
2. Presentations
3. Datasets

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

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

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

e. Pharmacometrics by ACCP

f. Regulatory Guidances

1. US FDA Population Pharmacokinetics [PDF]
2. 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

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

Let me know your thoughts if you enjoyed this video!

Good Modeling

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

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]

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A=X+Y+Z: Sucess Formula

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!