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Dear all,
Could anybody provide me with some examples of simulations replacing
the actual clinical studies? Reference to publications would be
highly appreciated.
Toufigh Gordi
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Toufigh
A recent paper from R. Miller et al shows how adequate exposure-
response analysis replaced a replicate clinical trial for
registration of gabapentin.
The reference is : Miller R, Ewy W, Corrigan BW, Ouellet D, Hermann
D, Kowalski KG, Lockwood P, Koup JR, Donevan S, El Kattan A, Li CS,
Werth JL, Feltner DE, and Lalonde RL (2005) How modeling and
simulation have enhanced decision making in new drug development.
J.Pharmacokinet.Pharmacodyn. 32:185-197.
Best regards,
Antoine DESLANDES, PhD
DMPK Senior Manager
CENTELION SAS
72-82 Rue Leon Geffroy
94408 VITRY SUR SEINE CEDEX
FRANCE
Phone (33).1.58.93.36.30
Fax (33).1.58.93.35.05
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Dear Toufigh
There's a review paper on this issue coming out still this year, so
I've heard, with an extensive reference list. Keep checking the
International Journal of Pharmaceutical Medicine.
Right away you may want to check out these:
Veyrat-Follet C, Bruno R, Olivares R, Rhodes GR, Chaikin P, "Clinical
trial simulation of docetaxel in patients with cancer as a tool for
dosage optimization", Clin. Pharmacol. Ther. 2000, 68:677-87
Nestorov I, Graham G, Duffull S, Aarons L, Fuseau E, Coates P,
"Modeling and stimulation for clinical trial design involving a
categorical response: a phase II case study with naratriptan" Pharm.
Res. 2001, 18(8):1210-9
Chabaud S, Girard P, Nony P, Boissel JP, "Clinical trial simulation
using therapeutic effect modeling: Application to ivabradine efficacy
in patients with angina pectoris", J. Pharmacok. Pharmacodyn. 2002, 29
(4):339-63
Agoram B, Rossi G, Heatherington AC, "Three-times-weekly
administration of darbepoetin alfa appears to be as effective as 100
\0x00g once a week in chemotherapy-induced anemia: Results of a
clinical trial simulation", J. Supportive Oncol. 2005, 3(2) Supl.1, 26-7
Ridder FD, "Predicting the outcome of phase III trials using phase II
data: A case study of clinical trial simulation in late stage drug
development", Basic Clin. Pharmacol. Toxicol. 2005, 96(3):235-41
Regards
Luis
--
Luis M. Pereira, Ph.D.
Assistant Professor, Biopharmaceutics and Pharmacokinetics
Massachusetts College of Pharmacy and Health Sciences
179 Longwood Ave, Boston, MA 02115
Phone: (617) 732-2905
Fax: (617) 732-2228
Luis.Pereira.at.bos.mcphs.edu
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There are several cases where simulations were utilized to make
regulatory
decisions related to approval and labeling across 42 NDAs. I am not sure
what you exactly mean by 'replacing', but the attached reference
might be of
help to you. We discuss case studies where simulations alleviated the
need
for additional trials and allowed approval of doses not directly
tested in
clinical trials...Joga
Please note the new address and phone below:
Joga Gobburu
Pharmacometrics, OCPB, FDA
10903 New Hampshire Avenue, Building 21, Rm. 4524
Silver Spring, MD 20993-0002
Ph: 301-796-1534
email: jogarao.gobburu.-a-.fda.hhs.gov
[The AAPS Journal 2005; 7 (3) Article 51 (http://www.aapsj.org)
Impact of Pharmacometrics on Drug Approval and Labeling Decisions:
A Survey of 42 New Drug Applications
Submitted: April 4, 2005; Accepted: April 29, 2005; Published:
October 7, 2005
Venkatesh A. Bhattaram,1 Brian P. Booth,1 Roshni P. Ramchandani,1 B.
Nhi Beasley,1 Yaning Wang,1
Veneeta Tandon,1 John Z. Duan,1 Raman K. Baweja,1 Patrick J. Marroum,
1 Ramana S. Uppoor,1
Nam Atiqur Rahman,1 Chandrahas G. Sahajwalla,1 J. Robert Powell,1
Mehul U. Mehta,1 and
Jogarao V. S. Gobburu1
1
Food and Drug Administration, Rockville, MD 20852 - db]
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I may be reading between the lines of the original posting too much,
but what I sense is that there is a desire to 'validate' the use of
clinical trial simulation by using examples where it has obviated the
conduct of a clinical trial. To me this is faulty logic and
unfortunately it is a theme that I repeatedly see. What you are
addressing in your question are organizational issues, not scientific
ones. Let me explain what I mean:
Data, historical knowledge, common sense, scientific judgement, and
hypothesis are combined to formulate a model. When the model is used
for a simulation it merely expresses the knowledge contained in the
model in what is frequently a more convenient expression than the
original form of the model. In other words, the simulation yields a
pretty picture.
Now over to the clinical drug development side, we run a clinical
study when our knowledge is insufficient with regards to one or more
aspects of a drug's performance. If we run a study that confirms a
prior simulation without adding new knowledge there is a good chance
that it was a wasted study.
If we obviate a clinical trial through the use of a clinical trial
simulation there can be a few interpretations:
1. The new expression of our knowledge (which by the way is
knowledge we already had) via simulation is so compelling that we
have a 'eureka' moment and all stakeholders share the epiphany thus
concluding the trial is not necessary.
2. A level of incompetence in the interpretation or evaluation of
the current state of knowledge exists, a trial is proposed, but it is
later concluded on the basis of a simulation that said trial is not
required.
3. Modeling and simulation is used continually to inform
stakeholders (clinical teams, FDA, investors, patients, etc...) about
the current state of knowledge and the clinical plan is adapted and
updated according to the current state of knowledge.
My impression is that you are looking for an example of Case #1. In
my experience, I have found these to be rare or nonexistent. Case #2
is a lot more common and I want be especially clear here to avoid
seeming arrogant or appear overly critical. I selected the word
"incompetence" carefully for its definition "lacking qualities
required to do a job" My feeling is that the industry on average
lacks key skills in quantitative pharmacology. However, all too
often the incompetence rests with us when we are unable to
communicate the complicated knowledge in our models in a timely or
convincing manner. There is vast room for improvement all 'round.
Accuse me of blue-sky thinking, but #3 is the goal we should be
working towards. In this case the poorly conceived trials never
achieve such a status as they must be overcome with simulations.
When we are in the "dragon slayer" role we have missed opportunities
early in the process.
So in a long-winded way, a case study where simulations were done
instead of a clinical trial may well be the result of poor decision
making early-on in the process. It is real hard to count up the
successes in the third paradigm, but in the end a more efficient and
productive clinical research pipeline is inevitable.
Regards, Jeff
PS Most of everything I have written above has already appeared much
more succinctly in the lyrics of a Bob Dylan song:
"If the point is sharp, and the arrow is swift, it can pierce through
the dust no matter how thick."
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Dear Jeff
No clinical trial simulation should be envisioned as a replacement
for actual clinical trials. I guess this is the writing on the wall
by all the many experts on the field. I personally think it is
paramount to make this perfectly clear.
Luis
--
Luis M. Pereira, Ph.D.
Assistant Professor, Biopharmaceutics and Pharmacokinetics
Massachusetts College of Pharmacy and Health Sciences
179 Longwood Ave, Boston, MA 02115
Phone: (617) 732-2905
Fax: (617) 732-2228
Luis.Pereira.aaa.bos.mcphs.edu
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Dear Luis,
I think this may be a matter of semantics. I agree with you in the sense
that no drug will ever be approved without clinical trials - at least
not in
my lifetime. But I think there are cases that you would also agree
could be
described as a simulation replacing a clinical trial.
For example, what if one can conclude with a high degree of
certainty, based
on simulation, that a proposed clinical trial will fail? In such a
case, I
believe the simulation has served as a replacement, because without
running
a real trial, knowledge was gained that allowed making a decision to
cancel
the trial. Perhaps a different trial would then be designed and
tested (via
simulation). For every candidate trial that is rejected, one could
say that
the simulation replaced a real failed trial. Without simulation, the
only
way to know would be to run those real trials.
The state-of-the-art today does allow such predictions in cases
where, as
Jeff pointed out, the knowledge is there, buried in the data, and the
simulation brings it to the surface. Monte Carlo simulations of sizeable
populations, based on the proper input data and the proper modeling
methodology, can provide useful estimates of likely variances in
pharmacokinetics and pharmacodynamics. Such estimates are not
perfect, (as
G. Box said, "All models are wrong, but some models are useful"), but
they
can be extremely useful.
Simulation is a powerful tool. Moreover, it is the only tool that can
enable
us to understand certain complex interactions among the many
phenomena that
govern oral absorption, pharmacokinetics, and pharmacodynamics.
Having come from simulation and modeling in the aerospace industry 30
years
ago, I am excited to see the awakening in the pharmaceutical industry
to the
merits of simulation and modeling. We know from experience that failed
clinical trials are the norm, not the exception. If we can fail a
significant number of them in the computer rather than in the field, the
savings of time and money could be immense. Those resources could
then be
directed toward exploring a larger number of candidates, which should
yield
a larger number of successes.
Best regards,
Walt
Walt Woltosz
Chairman & CEO
Simulations Plus, Inc. (AMEX: SLP)
1220 W. Avenue J
Lancaster, CA 93534-2902
U.S.A.
http://www.simulations-plus.com
Phone: (661) 723-7723
FAX: (661) 723-5524
E-mail: walt.at.simulations-plus.com
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Dear Luis,
regarding FDA or EMEA approvals I am sure (as everybody else I
presume) that we are not in the process of approving drugs that have
been "dosed in computers" for a human use.
But simulation is a very powerful tool to generate new hypotheses and
also to evaluate the relevance of scientific hypotheses and to
generate new ones for clinical trial design.
I have two different examples in mind but I am concerned I cannot
develop this :
- one where simulation generated different hypotheses with a
prioritisation for a clinical evaluation,
- the other one more recently and at a preclinical stage to generate
hypotheses on the prion disease.
Best regards,
Frederic Doc
ACRITER - drug discovery consulting
www.acriter-consulting.com
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Dear Walt and Frederic
Although it may not seem at a first glance, I totally agree with both
of you. And being this format certainly not the best to develop such
an interesting topic, I can only suggest the reading of "Critical
considerations about clinical trials simulation" in print by the
Int.J.Pharm.Med.
In a nut shell, what I meant is imbedded in Walt's words "knowledge
is there, buried in the data", and "proper input data". Precisely
because I'm an enthusiastic of modeling and simulation I get worried
with trade journals headlines such as "Models that take drugs" and
"You'll be simulated" by Stephan Herrera in The Economist, June 9th
2005, or "Drug testing with computer models" and "Software meets
Biology" by Karen Southwick in Forbes, July 10th 2002. Every
minimally useful simulation can only build up on prior
experimentation. The poorer the data, the least informative the
simulation (GIGO). There's really no such thing as free lunches. So
in terms of drug approval, Walt is perfectly clear. In terms of a 'No-
go' decision for a clinical trial, the usefulness of clinical trial
simulation is tremendous. But in my experience one may decide not to
go for a Phase III (saving tremendously precious resources) based on
simulations build up on Phase II, or the same for Ph.II versus Ph.I,
or even Ph.I versus preclinical, animal studies and allometric
extrapolations. Joga's paper (Bhattaram et al.) is very significant
about the regulatory decisions it describes. Allow me to also suggest
the several applications described in "Simulation for Designing
Clinical Trials" by Kimko and Duffull, Marcel Dekker, 2003.
In summary, I very much prefer the terminology 'computer-assisted
clinical trials' to the notion of replacing CT by simulations. There
is no turning back on scientific and technological advancements. I
just think that we can never forget the many instances in history
when wonderful breakthroughs ended up being used for questionable
applications and rendered painful results.
Yours truly
Luis
--
Luis M. Pereira, Ph.D.
Assistant Professor, Biopharmaceutics and Pharmacokinetics
Massachusetts College of Pharmacy and Health Sciences
179 Longwood Ave, Boston, MA 02115
Phone: (617) 732-2905
Fax: (617) 732-2228
Luis.Pereira.at.bos.mcphs.edu
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