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INTRODUCTION

Decrease in R&D productivity

R&D costs continue to rise

• The median cost of developing any NTD from phase 1 clinical trials to approval is $250 million
• Only 10% of drugs tested in phase 1 are ultimately approved
• The total R&D cost to well more than $2.5 billion for every NTD approved

Major driver of cost

• Failure to achieve safety or efficacy in phase 2 and phase 3 trials
• key contributor to the decline in R&D productivity.

Late phase predictions

Failure

• Preclinical models
  • Poor predictive value of preclinical models correlates with lack of efficacy in phases 2 and 3

Success

• Drug targets based on human genetic diseases
  • More likely to achieve success
• “fail fast” strategy
  • Small clinical trials that test PoC
  • Reduce phase 2 and phase 3 attrition rates

Decline in R&D productivity

• 3-year rolling averages for late-stage pipeline (estimates of peak sales)
  • Decreased by nearly 50% over the past 5 years
  • From $692 million (during the period from 2010 to 2012)
  • To $451 million (2013 to 2015)

I. CAUSAL HUMAN BIOLOGY

Definition of good drug

• “Good” drug
  • One that binds to and modulates a molecular target in such a way that is safe and effective in the disease context for which it is administered.
  • Safety-efficacy profiles and dose-response curves

Physiological outcome

• Target modulation is causally related to a physiological outcome
• Naturally occurring biologic perturbations that lead to changes in human physiology
  • Clues into the mechanisms by which new therapies might work
• Goal of drug R&D is to develop therapies that mimic experiments of nature
• These causal relationships should be established at the time a target is selected

Infectious diseases

• Infections of the lungs or skin
  • Pneumonia
  • Cellulitis
• Other diseases that were not considered initially to result from an infectious agent
  • Helicobacter pylori as a cause of gastric ulcers
  • Human papillomavirus as a cause of cervical cancer
• Therapeutic interventions against these infectious agents have a documented benefit on human health, which provides a modern-day test of Koch’s postulates.

Genetics and tissue-specific autoimmunity

• Experiments of nature
• Approved antipsychotic medications block dopamine receptor D2 (DRD2) and treat the positive symptoms in patients with schizophrenia.
• GWAS
  • Identified genetic variation in the DRD2 gene locus (increased risk)

Ongoing large-scale sequencing efforts

• genomes are linked to detailed clinical data
• Genotype-phenotype dose-response curves can be estimated at the start of a drug discovery program
• Gain of function (GoF) and loss of function (LoF), including “human knockouts”
  • Linked to clinical data that can be mined to estimate the effect of lifelong genetic perturbation on human physiology

Single-cell technologies

• Possible to identify antigens that drive the human immune response to infectious diseases, autoimmune disorders

Examples

• Neutralizing antibodies that recognize the hemagglutinin glycoprotein antigen from influenza A virus have been identified
• Antibodies against DRD2 in patients with schizophrenia

Animal models - Limitations

Valuable

• Understanding of complex physiology, testing pharmacology, and assessing safety

Lesson

• animal models should not be used to pick targets at the beginning of a drug discovery program
• Targets should be selected on the basis of a deep understanding of causal human biology, not on the basis of imperfect and notoriously inaccurate animal model data, whether causal or correlative.

II. THERAPEUTIC MODULATION

Therapeutic modulation - Two major challenges.

1. therapeutic molecule must gain access to the protein target

• Only ~20% of human proteins are accessible by either small molecules (which target hydrophobic pockets) or biological therapeutics (which bind to extracellular targets), which leaves most protein targets “undruggable” .

2. it must exert an effect consistent with the underlying therapeutic hypothesis.

• As a consequence, only a small portion of potential drug targets is considered therapeutically tractable for a new drug discovery program.

Therapeutic modulation - causal human biology

Directionality of the desired therapeutic modulation

• Therapeutically desirable to increase or decrease activity of protein target
• Altering enzymatic activity, ligand-induced receptor signaling, or transcriptional regulation).

Examples

• Narcolepsy
  • Autoimmune destruction of a specific cell type that secretes a specific protein ligand
  • Obliteration of neurons that secrete wakefulness-inducing orexin in patients with narcolepsy

Limitation of druggability so far

• Selected on the basis of tractability (or druggability) rather than causal human biology
• Many targets identified by human genetics or other experiments of nature might not be considered druggable by either conventional small molecules or biologics

Example - GBA

• Glucocerebrosidase (GBA), a lysosomal enzyme–encoding gene
  • Gaucher disease, Parkinson’s disease
• GBA breaks down glucocerebroside into glucose and ceramide, a fat molecule
• As an intracellular protein
  • Not accessible via conventional antibody-based biologics
  • Also challenging to achieve with a small molecule, indicating that a new approach to GBA targeting is needed

overcoming “undruggable genome”

beyond small molecules and monoclonal antibodies

• Positive allosteric modulators
• Conjugated nanobodies that bind different epitopes of a single target
• Phenotypic screens
• MRNA delivery
• Small interfering RNA
• Antisense oligonucleotides
• Gene editing with CRISPR
• Peptides

III. BIOMARKERS OF TARGET MODULATION

What is biomarker?

• One of the most difficult aspects of drug discovery
  • Making robust predictions about how drug concentration in the blood relates to the final clinical outcome
• The term “biomarker”
  • Biological readouts along the chain of events from the time a drug is exposed to the target (target exposure),
  • Engages with the target (target engagement),
  • modulates the target to exert a physiological effect in a human system (target modulation).

PD marker

• Most valuable pharmacodynamic biomarkers
  • Integrate blood and tissue pharmacokinetics
  • Target engagement into a biological readout that is feasible to measure in a clinical trial
• Conventional PD marker
  • Pharmacological perturbation on a biological system, but these measurements have no connection to disease-specific causal human biology
• In the translational medicine model proposed herein, a key step is to identify biomarkers that robustly measure the same physiological outcomes induced by experiments of nature in humans

LDL

• Low-density lipoprotein (LDL) cholesterol
• example of a robust pharmacodynamic biomarker linked to causal human biology through genetic association at the PCSK9 gene
• Human PCSK9 genetic variants that give rise to lower LDL cholesterol protect from risk of cardiovascular disease
• One important reason that the FDA approved two PCSK9 inhibitors
  • Alirocumab and evolocumab
  • LDL reduction is an accurate efficacy biomarker for protection against cardiovascular events

pharmacodynamic biomarkers linked with causal human biology

• Population-based resources
• link genetic data to deep, longitudinal molecular profiling and clinical data are being established
• United States–led Precision Medicine Initiative)

IV. NEXT-GENERATION POC TRIALS

Traditional clinical trials

• Clinical trials represent the ultimate test of a therapeutic hypothesis
• safety and tolerability in a phase 1 clinical study
• relationship between dose of a drug and biological activity (dose-response curves) in a phase 2 trial
• This stage is followed by a larger phase 3 trial to assess the safety-efficacy profile
• Traditionally each phase is conducted in series

Traditional vs Translational

Traditional clinical trial framework

• Infectious diseases
  • PoC can be achieved by observing viral-load reduction in very small cohorts of patients in phase 2
• Neurodegenerative diseases
  • PoC can be achieved only by observing changes in clinical outcome in phase 3 trials that involve thousands of patients

New clinical trial design - Linking these two

• Therapeutic modulation of targets anchored in causal human biology
• Pharmacodynamic biomarkers of target modulation

Next-gen POC trials

1 Identification of populations

• Selected patient populations can be identified for the clinical PoC study
• Ivacaftor in cystic fibrosis patients who carry specific genetic mutations

2 Selection of PD biomarker

• Pharmacodynamic biomarkers that are linked with causal human biology

Examples

• In developing an influenza vaccine, an immune response to hemagglutinin glycoprotein antigens is a robust pharmacodynamic biomarker
• As described above, LDL lowering, linked with human carriers of different PCSK9 mutations, is a powerful pharmacodynamic biomarker for PCSK9 inhibitors

Next-gen POC trials

3 Digital health technologies

• Patients can be followed outside of traditional clinical units using digital health technologies

Examples

• “digital pills”
  • Metal-coated tablets that dissolve in the stomach and communicate wirelessly with a mobile device),
• Continuous monitoring devices
  • Glucose-sensing contact lenses
• Consumer-based laboratory testing (such as smartphone kits)

Next-gen POC trials

4 Adaptive Trial Design

• Biomarker or clinical outcomes can be used to modify the design during the trial
• Powerful approach to connect causal human biology, biomarkers, and clinical PoC

Examples

• The breast cancer study I-SPY 2

V. LIMITATIONS OF THE PROPOSED MODEL

First and foremost

• There is an underlying assumption that we have sufficient data from humans
  • Validation of this assumption requires an ecosystem
  • Work systematically toward building such databases
• no single resource that enables systematic identification of human genetic variants linked to clinical outcomes
• no large population with detailed molecular longitudinal profiling to identify novel biomarkers

Second

• Experiments of nature are rarely perfect substitutes for pharmacological interventions
• However, a two- to threefold increase in the success rate during phase 2 or phase 3 would have substantial financial implications
• Failing in a large phase 3 study is about 10-fold more expensive than failing in a small clinical PoC study ($150 million versus $15 million per NTD)

Third

• Some diseases do not have experiments of nature to guide target selection
• Every complex disease is influenced by environmental, behavioral, or stochastic factors that might lead to specific therapeutic hypotheses
• Consistent with this observation, there are many examples of approved therapies that do not have obvious evidence of causal human biology

Fourth

• Quantitative models are needed to translate causal human biology into therapeutic hypotheses that can be tested via pharmacodynamic biomarkers or clinical outcomes in small PoC trials
• For example, human genetics might suggest that modulating a target will have a desired effect in humans, but genetic data might not indicate how much to modulate the target for a desired therapeutic window

Fifth

• New digital health technologies must enable clinical trial designs that test previously untestable therapeutic hypotheses

Summary and Conclusions

• Decreased productivity in therapeutics research and development (R&D)
  • Drug costs up while delivering insufficient value to patients
• Model of translational medicine that connects four components of the early R&D pipeline
  1. causal human biology
  2. therapeutic modality
  3. biomarkers of target modulation
  4. proof-of-concept clinical trials
• Technological advances and a disciplined approach
• This translational medicine approach will not eliminate all late-stage R&D failures—
• Drug discovery is an inherently risky business, after all—but it should help

Thank you. 감사합니다.