Sunday, July 25, 2021

Maximum Tolerable Dose (MTD) and Dose-Limiting Toxicities (DLTs)

According to Wiley Encyclopedia of Clinical Trials, the maximum tolerable dose (MTD) is defined as: 

The “Maximum Tolerable Dose” (MTD), also known as the “Maximum Tolerated Dose” or the “Maximally Tolerated Dose”, is defined as the dose that produces an “acceptable” level of toxicity or that, if exceeded, would put animals or patients at “unacceptable” risk for toxicity. Besides determining animal toxicology, establishing the MTD is the main objective of Phase I clinical trials, mostly in cancer and HIV treatment in which relatively high doses of drugs are usually chosen to achieve the greatest possible beneficial antitumor effect. Definition of the MTD usually relies on the sample, as MTD is defined as the dose level at which more than two patients over six experienced dose-limiting toxicity (DLT). More recently, the MTD has been defined as the dose that produces a certain frequency of DLT within the treated patient population. In this framework, the MTD is estimated from the data using Bayes or maximum likelihood inference. In all these designs, the MTD is established for one initial administration or treatment course of a cytotoxic experimental agent, ignoring efficacy. To address these issues, the maximum tolerated schedule and the most successful dose have been proposed to be used rather than a conventional MTD. Finally, the concept of MTD that uses toxicity as a surrogate endpoint for efficacy in cytotoxic Phase I trials has been also controversial. Interests in alternatives to MTD have gained recently when dealing with new cytostatic agents that may produce relatively minimal organ toxicity, compared with standard cytotoxics. New optimal doses should be defined in the near future.

The clinical trials with the objective of determining the MTD are designed as dose-escalation studies with patients enrolled into the low dose group and then gradually into the high dose group. The patients who are enrolled under the same dose level below to the same dose cohort. The determination of the MTD relies on the identification of the dose-limiting toxicities (DLTs). Prior to escalating the dose cohort, the safety and tolerability in the previous cohort will be assessed and evaluated. 

According to NCI, DLTs are defined as side effects of a drug or other treatment that are serious enough to prevent an increase in dose or level of that treatment. In early-phase clinical trials, DTLs are defined so that the escalation of the dose cohort to the higher dose level can be determined based on the observed # of DTLs, which are subsequently used to determine the maximum tolerable dose (MTD). 

The dose-escalation study for determining the MTD is the most common first-in-human study design in oncology studies. The DTLs are usually defined as grade 3 or above drug-related adverse events defined by the common toxicity criteria for AEs (CTCAE) maintained by the National Cancer Institute (NCI). 

In non-oncology studies, the CTCAE criteria can still be used to define DTLs. But we also see some non-oncology studies with the customer-defined DLTs criteria.

Here are some examples of how the DTLs are described in oncology clinical trials with MTD as the purpose.  

A Multicenter Phase I Gene Therapy Clinical Trial Involving Intraperitoneal Administration of E1A-Lipid Complex in Patients with Recurrent Epithelial Ovarian Cancer Overexpressing HER-2/neu Oncogene

Toxicity during therapy was categorized as unrelated to, probably, possibly, or definitely related to E1A lipid complex. The dose-limiting toxicity was defined as the highest dose at which at least 2 of the 6 patients experienced National Cancer Institute Common Toxicity Criteria grade 3 or 4 drug-related toxicity during the course of therapy. Maximum tolerated dose was defined at one dose level below dose-limiting toxicity

Intra-arterial administration of a replication-selective adenovirus (dl1520) in patients with colorectal carcinoma metastatic to the liver: a phase I trial
Dose escalation proceeded from 2 × 108 to 2 × 1012 particles without occurrence of any dose-limiting toxicities. Specifically, no treatment-emergent clinical hepatotoxicity occurred during dose-escalation, despite pre-existing liver abnormalities due to intrahepatic metastases in over half of the patients at baseline. Transient low grade (1– 2) transaminitis was documented in three patients (following single agent virus) and was classified by the investigator as ‘possibly attributable’ to ONYX-015 (6 × 1011 and 2 × 1012 particles); the laboratory abnormalities resolved within 12 days and did not reoccur after subsequent treatments. Four patients had liver-related adverse events reported (hyperbilirubinemia) that were classified as ‘unrelated’ to ONYX-015 and were associated with intrahepatic tumor progression. The highest dose administered (2 × 1012 particles) was shown to be well-tolerated in three patients. The 2 × 1012 particle dose level therefore appears to be well-tolerated, and the maximum dose that could be administered based on manufacturing capabilities was the MTD for the study

Redefining Dose-Limiting Toxicity

Dose-limiting toxicities (DLTs) traditionally are defined by the occurrence of severe toxicities during the first cycle of systemic cancer therapy. Such toxicities are assessed according to the National Cancer Institute’s Common Terminology Criteria for Adverse Events (CTCAE) classification, and usually encompass all grade 3 or higher toxicities with the exception of grade 3 nonfebrile neutropenia and alopecia. This broad definition dates back to the development of conventional cytotoxic chemotherapeutic agents, and is not applicable to the toxicity profile of modern molecularly targeted therapies (MTTs), which now constitute the vast majority of drugs evaluated in phase 1 trials. Despite this shift in drug development, the old definition of DLT is still used for most clinical trials. However, a few clinical trials are beginning to update their definition of DLT, and now tend to add variations to that common DLT definition backbone. The most frequent changes include the addition of some a priori untreatable or irreversible grade 2 toxicities (eg, neurotoxicities, ocular toxicities, or cardiac toxicities), prolonged grade 2 toxicities (ie, grade 2 toxicities lasting longer than a certain period), or the prolongation of the DLT period. However, these changes are still rare and most phase 1 clinical trials still use the traditional DLT definition.

Lenalidomide in Treating Patients With AIDS-Associated Kaposi's Sarcoma
Toxicities will be graded according to the National Cancer Institute (NCI) Common Terminology Criteria for Adverse Events (CTCAE) Version 4.0. Using a 3+3 design, the MTD is defined as the level at which 0/6 or 1/6 patients experiences at dose-limiting toxicity in the first cycle.

Here are some examples of how the DTLs are described in non-oncology clinical trials with MTD as the purpose.  

The LIPid Intensive Drug Therapy for Sepsis - Pilot (LIPIDS-P) Phase I/II Trial
LIPid Intensive Drug therapy for SepsisPilot (LIPIDS-P): Phase I/II clinical trial protocol of lipid emulsion therapy for stabilising cholesterol levels in sepsis and septic shock

Safety and Tolerability Study of Allogeneic Mesenchymal Stem Cell Infusion in Adults With Cystic Fibrosis (CEASE-CF)

Dose limiting toxicity (DLT), triggered by occurrence in the first 24 hours after hMSC infusion of grade ≥3 infusion-related allergic toxicities [ Time Frame: 24 hours ]

 Phase 1b Study of PD-0332991 in Combination With T-DM1(Trastuzumab-DM1)

Toxicity will be assessed using the Common Terminology Criteria of Adverse Events (CTCAE) version 4.0 grading scale. Dose- limiting toxicity-DLT is defined as any drug-related grade 3 non-hematologic toxicity or grade 4 hematologic toxicity lasting >28 days after the last day of therapy. If two patients experience drug-related DLT, the maximal tolerated dose (MTD) for the combination in HER2-positive breast cancer patients has been exceeded, enrollment to that dose will stop, and the next lower dose will be designated the MTD. An additional 15 patients will be treated at the MTD or the maximal 200mg po daily PD-0332991 dose in combination with T-DM1 to confirm safety. Treatment cycles will continue until disease progression or withdrawal from study.
Histone Deacetylase Inhibitor LBH589 in Addition to Corticosteroids in Patients With Acute Graft Versus Host Disease (GVHD)
Dose limiting toxicity (DLT) is defined by the occurrence of Common Toxicity Criteria (CTC) grade 3 or greater toxicity that is unexpected with transplantation, except for hematological toxicity, where DLT is defined as absolute neutrophil count (ANC) <750, and for those participants who were platelet transfusion independent is defined as platelets <10 K.
We can identify the clinical trials on with the purpose of identifying the MTDs and DLTs. The vast majority of these studies are oncology studies or studies in serious conditions - these studies are usually conducted in patients (not healthy volunteers) and must be registered on even it is a phase I study - the phase I studies in healthy volunteers are exempted from the registration. 

Sunday, July 18, 2021

Imputation of partial dates for adverse events, concomitant medications, and disease diagnosis

Many date variables are collected in the clinical trial database. The date variables include date of birth, date of disease diagnosis, date of medical history onset, start and stop date of adverse events, start / stop date of concomitant medications, ......

It is not uncommon that the partial dates may be collected where the partial dates mean that at least one of the components (day, month, or year) is missing. 

Partial date for date of birth is not because the subjects don't remember their birth date, is because the data security law prevents the sponsors from collecting the date of birth information in certain countries (especially in Germany). 

In statistical analyses, the partial dates need to be handled or imputed for the purpose of allocating the event (adverse events, concomitant medication) into the appropriate categories (treatment-emergent adverse events, prior medications, concomitant medications added during the study,...) or calculating the duration of the events (duration from the disease diagnosis to the study start).

For clarity, the algorithm and rules for imputing the partial dates need to be specified in the statistical analysis plan (SAP). There is no regulatory guidance about which algorithm and rules will be appropriate when imputing the partial dates. Different companies may have different rules when imputing partial dates. In general, the rules will be adequate as long as it is on the conservative side, for example, if an adverse event has a partial or missing start date and can't be determined if it occurs before the first dose of the study drug, the adverse event will be classified as 'treatment-emergent adverse event'. 

Partial date imputation is always a single imputation - the missing day or missing month will be replaced with a fixed day or month based on the imputation algorithm. The candidates for replacing the missing day could be: the first day of the month, the last day of the month, the day of the first dose of the study drug. The candidates for replacing the missing day and month could be Jun 30 of the year or July 1 of the year. 

Usually, if all day, month, and year are missing, the missing date will not be imputed. The adverse events with missing onset date will be classified as 'treatment-emergent AEs' and the concomitant medication will be classified as 'on treatment medications' (i.e., to be included in summaries of concomitant medications during the study). 

Below are a list of algorithm and rules for imputing the partial dates for adverse events and concomitant medications:

In an SAP for a Pfizer phase I study, if the day of the month is missing, the 1st day of the month is used. 

In a Novartis study SAP, the rather complicated algorithm was proposed for imputing the partial dates for adverse events and concomitant medications:

In a study by Johnson & Johnson, the appended SAP specified the rules for imputing the partial dates for adverse events, concomitant medications, and for disease diagnosis as the following: 

In a study by ChemoCentryx in NEJM, the appended SAP described the imputation rules for partial dates for adverse events and concomitant medications as the following: 


In the paper "Partial Dates; decisions and implications of handling partially missing dates" by Bowman, the following rules were stated for imputing the partial dates for adverse events and concomitant medications. 

Missing Adverse Event Start and Stop Dates date:

There are two options available. The partial start date may be set to the first of the month or to equal the study medication start date. As previously discussed, the first option would indicate the adverse event began prior to the study medication. However, the second option, setting the start date of AE1 to the study medication start date will suggest the adverse event had a short duration, as the adverse event end date is also defined as June 2006, but began during the treatment period of the study drug. Although the second option is not ideal, as AE1 may have had a longer duration, it is more conservative to associate the adverse event start with a date during study medication. Another solution to consider is not to impute a date at all but merely to assign a study phase to the start of the adverse event. In this example, a phase of "treatment" could be allocated to the start of teh adverse event, which would ensure it was classed most conservatively, without defining an actual date to the start of the adverse event. 

Concomitant Medications:

Subject has a partial concomitant medication start date of “--Apr2006” (see figure 1). As discussed above, missing start dates may be set to the first of the month, which is shown under option 1. However, this then pushes the concomitant medication to starting before the first dose of the Study Medication (15Apr2006) and would suggest that the Study Medication had no involvement with the concomitant medication being taken. Is this really the most conservative approach? If not is there an alternative? The missing concomitant medication start date could be set to equal the first dose of Study Medication, options 2. This option allows the concomitant medication to be classed as an on-treatment medication, and is therefore the most conservative.  

Monday, July 12, 2021

Human Plasma-derived Products - Protein Therapies for Rare Diseases

I recently listened to a podcast from NPR's planet money "Blood Money". It discussed why only the U.S. and a few other countries allow companies to pay people for blood (or precisely the plasma) - the materials for many life-saving protein therapy products for rare diseases. Please listen to the podcast or read the transcripts of the podcast. 

Blood Money

We all heard or experienced blood donation which is usually voluntary by the donor with no monetary incentives. The Plasma donation is different and donors are paid for donating their plasma. So the first question we need to know what the difference between the (whole) blood and the plasma. Here is a table for comparison:

Whole Blood


This red bodily fluid is composed of red cells, white cells, plasma, and platelets. It supplies oxygen and essential nutrients to cells and tissues in the body and removes waste materials like carbon dioxide and lactic acid.Plasma is the clear, straw-colored liquid component found in the blood. It is made up of 90% water and carries nutrients, minerals, hormones, and proteins to parts of the body that need it. Plasma also contains antibodies that help fight infections and proteins including albumin and fibrinogen that help maintain serum osmotic pressure.
With red cells, white blood cells, and platelets in itWith red cells, white blood cells, and platelets removed


plasma is collected through a process known as plasmapheresis. Plasmapheresis is a method of removing and separating plasma from whole blood via an apheresis machine.

After Plasma is separated from the whole blood, the red blood cells and other cellular components are returned to the doner’s body
Whole blood is commonly transfused in its original form in an effort to treat injuries and illnesses. It can be also be separated into its individual components and used to treat conditions including cancer and blood disorders.Plasma, on the other hand, is typically used as a starting material to manufacture commercial drugs known as plasma-derived products. These plasma-derived products serve as lifesaving therapies for patients living with immune deficiencies and autoimmune diseases.

Human plasma is a treasure and contains many enzymes and antibodies that can be extracted and manufactured as medicines for many rare diseases. Human plasma products (also called plasma-derived products or fractionated plasma products) are highly regulated by the FDA - Office of Blood Research and Review under the Center for Biological Evaluation and Research (CBER). The drugs manufactured from human plasma (so-called plasma-derived products) need to go through the same process as other biological products and Biological License Application (BLAs) needs to be approved by the FDA for market authorization. Human plasma-derived products have been approved to be used in treating diseases in various indications in immunology area, enzyme replacement/augmentation therapies, neurology, pulmonary, hemostasis, ...... Some examples are:

  • Alpha-1 antitrypsin deficiency (A1AD)
  • Primary Immunodeficiency (PI)
  • Chronic Inflammatory Demyelinating Polyneuropathy (CIDP)
  • Guillain-Barré syndrome (GBS)
  • Hemophilia
  • Rabies
  • Hepatitis B
  • Kawasaki disease

The blockbuster product from the plasma fractionation is immunoglobulin (IVIG or SCIG). immunoglobulin is a life-saving product for primary immunodeficiency patients. Immunoglobulin is also thought to be a panacea for all kinds of neurological diseases (CIDP, GBS, Myasthenia Gravis, multifocal motor neuropathy) that some of which have no other efficacy treatments. 

Many of these diseases treated with plasma-derived products are orphan diseases or ultra-orphan diseases.

Theoretically, plasma-derived products have a risk of carrying bloodborne pathogens (viruses and other pathogens). However, these pathogens are destroyed or filtered out during the manufacturing process. The actual plasma-derived products are very safe - at least in the United States. 

For clinical trials with plasma-derived products, the following points are noted: 

  • Similar to the oncology drugs, the plasma-derived products can not be tested in healthy volunteers. Even for the first-in-human trial, the plasma-derived products will need to be tested directly in the patients.  
  • The study procedure will always need to include the virus tests at screening and possibly the following up visits. 
  • Always include the immunogenicity assessment (because the plasma-derived products are large protein therapies)
  • The design and analyses of clinical trials are the same as other drugs or biological products. For ultra-rare diseases, the single-arm design may be used as the pivotal study and the sample size can be very small. See FDA Approves First Ever Treatment for Plasminogen Deficiency Type 1 based on a single-arm study with 15 adult and pediatric patients with plasminogen deficiency type 1.
  • For pharmacokinetic analysis, the pre-dose drug concentration is not zero since there are endogenous compounds (i.e., enzymes or antibodies that are generated by the patients). 

Useful Links: 

Sunday, June 20, 2021

Early Phase Trial to Find Maximal Tolerated Dose (MTD) - 3+3, CRM, and BOIN Designs

In early-phase clinical trials, determining the dose range and therapeutic window is critical. The purpose of the early-phase studies may just be to identify the maximum tolerated dose or maximum tolerable dose. 

Definition of maximum tolerated dose (MTD)
The highest dose of a drug or treatment that does not cause unacceptable side effects. The maximum tolerated dose is determined in clinical trials by testing increasing doses on different groups of people until the highest dose with acceptable side effects is found. Also called MTD.
The studies for identifying the MTD are usually designed as a dose-escalation study and the dose-escalation study is defined as:
A study that determines the best dose of a new drug or treatment. In a dose-escalation study, the dose of the test drug is increased a little at a time in different groups of people (also called cohort) until the highest dose that does not cause harmful side effects is found. A dose-escalation study may also measure ways that the drug is used by the body and is often done as part of a phase I clinical trial. These trials usually include a small number of patients and may include healthy volunteers.

In dose-escalation studies, within each dose cohort, a placebo group can be included even though the majority of the dose-escalation studies for MTD are designed without placebo controls.

Identifying MTD is based on the number of dose-limiting toxicities (DTLs)that are observed in each dose cohort. DTLs are defined as: 

side effects of a drug or other treatment that are serious enough to prevent an increase in dose or level of that treatment.

In practice, DTLs are often defined as grade 3 or above adverse events according to Common Terminology Criteria for Adverse Events (CTCAEs) especially in the oncology area even though other customer-defined criteria for DTLs may be used in non-oncology areas. 

Clinical trials to identify the MTD are generally needed for phase I studies directly conducted in patients, not healthy volunteers. Areas that the phase I studies are conducted in patients, not healthy volunteers, include oncology drugs, drugs in severe diseases such as AIDS, Sepsis, ARDS, etc., the gene and cell therapies, human-plasma derived products.

There are different types of clinical trial designs for identifying the MTD. The commonly used designs are 3+3 design, Continuous Reassessment Method (CRM), and Bayesian Optimal INterval design (BOIN). 

3+3 Design was discussed in an early post Phase I Dose Escalation Study Design: "3 + 3 Design". It is a straightforward rule-based method and requires no statistical calculations. 3+3 design is the most frequently used method for identifying the MTD. 

The CRM is a model-based design for phase I trials, which aims to find the maximum tolerated dose (MTD) of a new therapy. The CRM has been shown to be more accurate in targeting the MTD than traditional rule-based approaches such as the 3 + 3 design. With CRM design, statistical inferences on the model parameter(s) need to be made using likelihood-based or Bayesian approaches and DLT probability at each dose needs to be estimated. The patient is assigned to the next dose level based on the probability of patients with DLTs at the current dose level. The toxicity risk of other dose levels is based on accrued data, which improves trial efficiency. 

Following articles or videos provided a great introduction/reference about the CRM method: 

The BOIN design shares the simplicity of the 3+3 design, which makes the decision of dose escalation/de-escalation by comparing the observed DLT rate with 0/3, 1/3, 2/3, 0/6, 1/6, and 2/6. The BOIN design makes the decision by comparing with two fixed boundaries, λe and λd, which is arguably even simpler.

BOIN design are described and explained in the following article and video:
Software for Sample Size Calculation for Phase I MTD Finding Studies:
  • is a website developed and maintained by a research team at MD Anderson Cancer and it contains the literature and software for phase I designs including CRM and BOIN. 
Additional Videos: 

Saturday, June 19, 2021

About Controversial Approval of Biogen's Alzheimer Drug

Two weeks ago, the US Food and Drug Administration (FDA) approved aducanumab (brand name Aduhelm) as a treatment for Alzheimer's disease -- a historic decision not because it addresses the longstanding unmet medical need for a safe and effective cure of a devastating disease that affects nearly 6 million Americans, but because of the unprecedented irregularities of the agency's actions, undermining its mission to protect public health and ensure the "safety, efficacy, and security" of treatments made available in the United States. 

The winner is obviously the drug developer, Biogen and its collaborator Eisai. They probably never thought that FDA would be so collaborative and more desired to approve aducanumab than the sponsors themselves. They rescued a drug that had been declared 'unlikely' to work (futility) just two years ago. They got an unlimited label for all Alzheimer patients (beyond the early Alzheimer patients that were studied in their clinical trials). They can decide on the drug price whatever they want because there is no price control in the US once the drug is approved by the US FDA. They have at least 9 years to complete the post-marketing confirmatory study. There are no incentives for them to complete this confirmatory study as early as possible. The longer the study takes, the more time they can make the money from a drug with unproven efficacy. 

The losers include a long list: 
  • FDA - loses its credibility
  • Alzheimer's patients - are given false hope and may end up taking 'snake oil' for many years down the road
  • Patient Advocacy Group - Alzheimer's Association was unhappy with Biogen's $56,000/year/patient price tag. 
  • Medicare/Medicaid/Insurance Companies - extremely high cost associated with Aduhelm ($56,000/year/patient) and the broad label for Aduhelm can cost them a lot of money
  • FDA Adcom Committee - insulted by FDA's decision to approve even though the Adcom voted overwhelmingly against the approval
  • Regulatory science - FDA has touted for years about the regulatory science and the strict rules to be followed for drug approval - these rules are not followed by the FDA - what can you do?
  • FDA statisticians - It is clear that the FDA statistical reviewers had their dissenting opinions and questioned the data / results from two pivotal studies that were prematurely discontinued due to futility. Statisticians' opinions were overruled. 

Usually, approval like this will be heralded as historical and celebrated by all parties - not this time for aducanumab approval. The reactions are overwhelmingly negative. Here is a list of articles discussing the controversial approval from different angles.  
In approving Biogen's aducanumab, the boundaries between the FDA (as a regulator) and the sponsor (as a drug developer) were crossed. In the drug development field, the sponsor will try everything to exaggerate the benefit and minimize the side effects while FDA will need to be on the conservative side, tamper down the expectations, prevent the manipulation of the data and biases in data analyses,...  In the aducanumab case, FDA is determined to approving the drug no matter what and no matter whether the data/ results from clinical trials have demonstrated "Substantial Evidence of Effectiveness". FDA retrospectively find a regulatory pathway (accelerated approval pathway) for approval. In doing so, FDA failed to stand by the standards it established and both regulators and sponsors had followed.

In the drug development field, pre-specification is critical. The regulatory pathway, the number of clinical trials for clinical development program, the clinical trial design, study endpoints, and statistical analysis plan have to be discussed and agreed upon with FDA. As Eli Lilly's CEO said that in drug development, "where the gold standard for approval is you call your shot, and then you hit your shot, like Babe Ruth pointing at the left-field and then hitting his home run there." The sub-group analyses and post-hoc analyses are for hypothesis-generating and can not be used to support the regulatory approval. In Biogen's case, it is obvious that an additional clinical trial is needed before the approval. By switching to the accelerated approval pathway, FDA essentially agreed that the pivotal studies with cognitive and function measures provided insufficient evidence for approval and they had to retrofit to find accelerated approval that is based on the biomarker (amyloid).

In a letter from FDA to AdCom about switching to the accelerated approval pathway, Dr. Billy Dunn said this: 
Following the advisory committee meeting, further discussion within FDA considered the uncertainty introduced by the conflicting results of Study 302 and Study 301 and the committee’s discussion of that uncertainty. Our discussions raised further consideration of the accelerated approval pathway; a topic discussed earlier in the development program but not directly discussed during the advisory committee meeting given the focus at that meeting on the evidence of clinical benefit. As you may be aware, the accelerated approval pathway is for drugs to treat serious diseases that are expected to provide a meaningful advantage over available therapy, but where there is residual uncertainty regarding the drug’s ultimate clinical benefit. To be approved under this pathway, there must be substantial evidence of the drug’s effectiveness on a surrogate endpoint—usually an endpoint that reflects the underlying disease pathology (accelerated approval can also use an intermediate clinical endpoint). An effect on this surrogate endpoint must be shown to be reasonably likely to predict clinical benefit. We concluded that these requirements were met for aducanumab, with substantial evidence that the drug reduces amyloid beta plaque, and that this reduction is reasonably likely to predict clinical benefit. For drugs approved using the accelerated approval pathway, further study is required to verify anticipated clinical benefits
FDA is preoccupied and determined to approve aducanumab no matter which pathway is used. The following conclusion is subjective and a lot of people will certainly not agree: "We concluded that these requirements were met for aducanumab, with substantial evidence that the drug reduces amyloid-beta plaque, and that this reduction is reasonably likely to predict clinical benefit." Had the FDA been so sure about the biomarker 'amyloid-beta plaque' reduction is 'reasonably likely to predict clinical benefit', they would advise the sponsors (Biogen and other Alzheimer drug developers) to design their phase III studies with the primary efficacy endpoint being the lowering the amyloid-beta plaque, not the measuring the benefit in improving the cognitive and function. 

Accelerated approval pathway is described in FDA guidance for industry "Expedited Programs for Serious Conditions – Drugs and Biologics", but is only used in a situation where the confirmatory studies with clinical endpoints have not been conducted. In Biogen's case, two confirmatory studies with clinical endpoints had already been completed (actually was stopped early for futility). It is a round peg in a square hole to retrospectively going back to the accelerated approval pathway based on the biomarker because of the conflicting and unconvincing results from confirmatory trials with clinical endpoints. Approval of aducanumab based on an accelerated approval pathway breaks agency precedent. "Accelerated approval is traditionally used for treatments that haven't yet proved themselves in large trials. In Biogen's case, Aduhelm went through two Phase 3 studies and came up with conflicting evidence."

FDA also loses its fairness - there are a lot of diseases with unmet medical needs. The drugs for other unmet medical conditional have been tested and generated stronger evidence than Biogen's pivotal studies, but the drugs were rejected by FDA. Here is an article about ALS (amyotrophic lateral sclerosis) - more deadly than Alzheimer's disease.

FDA's controversial Aduhelm decision leaves ALS patients feeling spurned

The FDA's controversial approval of Biogen's Aduhelm drug for Alzheimer's disease has been met with fierce resistance from all corners of the biopharma industry, but few seem to be as upset with the decision as ALS patients and advocacy groups.

For all that's already been written and discussed about the agency's announcement, from the drug's exorbitantly high price of $56,000 per year to criticism over lowered standards, ALS patients see something more. ALS patients and associations say they largely regarded Aduhelm's approval as a bittersweet double standard: happy that those with Alzheimer's have a new drug available, but questioning how the FDA evaluated Biogen's drug compared to the experimental programs being studies for their own disease. 

Nothing punctuated the feeling harder than the agency's announcement in April that a promising drug under development by the biotech Amylyx would need another study to confirm efficacy. This program, called AMX0035, hit the primary endpoint for improving function specifically laid out in the FDA's 2019 guidelines for new ALS treatments, whereas Biogen halted two pivotal Aduhelm studies early because of futility in its own function measurements. 

In general, to demonstrate substantial evidence of effectiveness of the drug, two adequate and well-controlled trials are needed. In Biogen's case, two adequate and well-controlled trials ENGAGE and EMERGE to evaluate the efficacy and safety of aducanumab in patients. When two studies gave contradicting results (one positive and one not positive), a third adequate and well-controlled study will be needed (before the drug approval, not after the drug approval). I remembered other examples: Pirfenidone was developed for treating the rare disease of IPF (idiopathic pulmonary fibrosis). The sponsor conducted two pivotal studies with one study positive (p=0.01) and one study negative (p=0.5). Initial NDA submission with these two studies was rejected by the FDA. FDA demanded the sponsor to conduct a third study. A third study gave a positive result (p<0.01) and NDA was resubmitted, and FDA approved the Perfenidone for IPF. Another example is ciprofloxacin dispersion in non-CF bronchiectasis (rare disease without approved treatment). The sponsor conducted two identical phase III studies ORIBIT-3 and ORBIT-4 - two studies gave contradicting results (one positive and one not positive). The NDA was rejected by FDA and additional studies were not conducted due to funding issues - ciprofloxacin dispersion remains not approved for non-CF bronchiectasis. 

In Biogen's case, two years have passed since they revealed the results of their pre-maturely discontinued studies: one with positive and one with negative. They could have started the third study and would be able to complete the third study not far from now. Instead, with FDA's help, they got their aducanumab approved without doing the third study and they were given a long 9-years to do a post-marketing phase IV study.


Tuesday, June 01, 2021

Decentralized clinical trials and in silico clinical trials

These days, the buzzword in the clinical trial field is 'decentralized clinical trials' or DCTs. The Covid-19 pandemic seems to push the clinical trials toward 'decentralized' or 'hybrid' of decentralized and traditional clinical trials. 

Traditional clinical trials are 'centered' around the clinical trial sites and the investigators. The patients (clinical trial participants) are recruited by the investigators who are the medical doctors responsible for the conduct of the clinical trial at trial sites. The trial sites are the clinics, hospitals, and medical centers. The patients would need to visit the trial sites regularly to see the investigators for clinical trial activities (signing the informed consent, screening for eligibility, receiving study treatments, performing efficacy and safety measures,...). The clinical trial data will then be recorded and entered into the database (for example EDC) by the study coordinator or investigator at investigational sites.

Decentralized clinical trials are defined as the decentralization of clinical trial operations where technology is used to communicate with study participants and collect data and the data collection will not depend on the frequent patient's visits to the investigational sites. According to CTTI (clinical trial transformation initiative) Recommendations: Decentralized Clinical Trials
DCTs using telemedicine and other emerging and novel information technology (IT)
services offer the potential for local HCPs to participate in clinical trials. This may
provide several advantages compared to traditional clinical trials conducted at more
centralized clinical trial sites, including the following:
  • Faster trial participant recruitment, which can accelerate trial participant access to important medical interventions and reduce costs for sponsors.
  • Improved trial participant retention, which may reduce missing data, shorten clinical trial timelines, and improve data interpretability.
  • Greater control, convenience, and comfort for trial participants by offering at home or local patient care.
  • Increased diversity of the population enrolled in clinical trials.
  • An opportunity for home administration or home use of the IMP, which may be
  • more representative of real-world administration/use post-approval.
FDA's Advancing Oncology Decentralized Trials - Learning from COVID-19 Trial Datasets also listed the advantages of the DCTs: 
  • Decentralized Clinical Trials (DCT) may have several potential benefits including reduced patient and sponsor burden and increased accrual and retention of a more diverse trial population.
  • Use of full or hybrid DCT designs by commercial sponsors has been rare in oncology, in part due to uncertainty surrounding the effect of remote assessments on data quality and outcomes.
  • COVID-19 has necessitated DCT-type trial modifications such as remote assessments to reduce patient exposure to COVID-19 infection from travel to trial sites.
  • Many of these remote assessment modifications were deployed in the middle of large ongoing cancer trials.
  • There is an opportunity to evaluate the effect of remote assessments on trial data to advance Decentralized Trials in oncology.
  • Better understanding of the effect of DCT modifications can reduce uncertainty for sponsors and regulatory bodies, and identify mitigation strategies for future prospective DCT designs.
Historically, DCTs may be called differently: virtual trials, siteless trials, remote trials, digital trials, direct-to-patient trials. These different names may just describe one specific aspect of the DCTs and can cause confusion. For example, 'virtual trials' can be confused with the in silico trials which are based on computer models and do not use real participants (patients) but computer programs to model participants to assess drug efficacy and safety during the preclinical phase or before a traditional trial.

In essence, in traditional clinical trials, we bring the trial to the patients; in DCTs, we bring the patients to the trial.

There are still a lot of challenges and obstacles to implementing decentralized clinical trials. Application of DCTs may be limited to some special situations (such as post-marketing studies with patient-reported outcomes and outcomes measured digitally). It is still rare for pivotal and registration studies to use full DCTs. It seems to be more appropriate to adopt hybrid trials - the combination of the traditional and the decentralized trials. For example, in clinical trials in the rare disease area, it is difficult for patients to travel to the investigational sites, the patients may visit the investigational sites for some important visits (in-clinic visits) and then the home health care nurses may be used for in-home visits to patient's home.  

In 2019, Janssen, PRA Launch a Fully Virtual Trial (it should be called the decentralized trial) "A Study on Impact of Canagliflozin on Health Status, Quality of Life, and Functional Status in Heart Failure (CHIEF-HF)". The study design was described in the Circulation: Heart Failure "Novel Trial Design: CHIEF-HF". CHIEF-HF seems to be the first phase III trial being fully decentralized.
Here are some references for DCTs:   
The decentralized clinical trials still collect the data from the patients and should not be called 'virtual clinical trials'. On the contrary, the 'In Silico clinical trials' is more appropriately called 'virtual clinical trials' or 'patientless clinical trials' and it simulates the virtual subjects for modeling and prediction. In Silico clinical trials may use the data from pre-clinical and historical clinical trials for simulation but involves no real patients in the study.  

ADMINISTRATION, AND RELATED AGENCIES APPROPRIATIONS BILL, 2016", In Silico clinical trials use computer models and simulations to develop and assess devices and drugs, including their potential risk to the public, before being tested in live clinical trials."

In Silico clinical trials are part of the model-informed drug development (MIDD). the FDA has a MIDD pilot program managed by the Division of Pharmacometrics

Dr. Yaning Wang has multiple presentations promoting the MIDD and In Silico clinical trials, for example, in his presentation at the 2021 FDA Science Forum "Regulatory Applications and Research of Model-Informed Drug Development (MIDD)" (Youtube video at 2:38:25) and in his presentation at PMDA "Application of MIDD in New Drug Development and Approval". 

Here are some additional references on In Silico clinical trials:

Saturday, May 29, 2021

Patient Advocacy Groups in Drug Development and Clinical Trials For Patients With Rare Diseases

I just saw an article on "Best Practices For Designing And Running Clinical Trials For Patients With Rare Diseases" by my previous colleague, Mary L Smith. 

She had some excellent points about the important role of the patient advocacy group in the drug development process in rare disease areas.

Now that the drug development has been moved to the patient-centric, the patient's voice (usually through the patient advocacy group) is critical. Over the years, I have seen or directly interacted with some of the patient advocacy groups in various activities.

We saw that the patient advocacy group (i.e played a critical role in pushing FDA to approve the first drug for Duchenne Muscular Dystrophy even though there wasn't substantial evidence to support the efficacy. 

Cystic Fibrosis Foundation is probably the most successful patient advocate group and it is very well run and organized. In the US, it is extremely to do any clinical trials in CF patients without going through the Cystic Fibrosis Foundation. Cystic Fibrosis Foundation may also be the richest patient advocacy group and received a lot of money from the royalties from CF drug developers. 
In conducting the clinical trials in patients with Alpha-1 antitrypsin deficiency (a genetic form of severe COPD), we were very closely working with Alpha 1 Foundation - a patient advocacy group created by three Alpha-1 Antitrypsin Deficiency patients.  Alpha-1 Foundation's help pushed FDA/NIH to organize the workshops to discuss the efficacy endpoints that are realistic in clinical trials in Alpha-1 Antitrypsin patients. One of the endpoints was to measure the lung density through CT scan - so-called lung densitometry that was eventually accepted by the FDA to be the primary efficacy measure in Alpha-1 Antriypsin Deficiency trials.   

Other examples of patient advocacy groups are: