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It is looking very possible that I took
Blarcamesine’s post of hiring Pharmavigilance .. and when the discussion turned to sales
Misappropriated that position to sales..
Perhaps in reviewing positions my eyesight saw senior as sales..
I still recall someone saying there was a position for National Sales Director but I can not find post..
Will request my other posts be removed
Plex
Here is snapshot of hiring from anavex site: there was a quick exchange on IHUB
Showing position than it was gone..
Trying to back through.. someone said they had screen shot.. trying to find chain..
grenings
LIFE SCIENCES Corp.
Director/Senior Director. Biostatistics
Senior/Exective Director, Clinical Development & Medical Evidence
Director/Senior Director/Executive Director. Clinical Development
Associate Director/Director/ Senior Director. Clinical Scientist
Vice President, Quality Assurance
Director/Senior Director/ Executive Director. Clinical Operations
Q
Director/Senior Director/ Executive Director. Global Pharm
Submit resumé for the record
Equal Employment Opportunity
What is the sales director going to do?
Anavex has no products approved for sale? Why would you take on that cost..
Unless you knew..
They know
It would make zero sense to hire salespeople and global safety directors
Unless you are very very close
Somebody Google when a BioPharm should hire a sales director
With that in mind
Only
Only with a VERY very positive mindset
with intimate knowledge of succesful data
Would such a company take on
ALL the overhead associated with multiple high pay employees..
Including Director of Sales( which don’t exist)
Surprised we not past $25
Pumping ?
Prophylaxis is the word the Company uses.
They have access to all OLE data..
This board is calm and respectful..
Too bad all shorts are about to get financially Destroyed.
Just kidding
Exactly..
BP isn’t needed..
Why hire global event director?
Because you going to be managing a lot
Of scripts from all over..
They aren’t going to have a problem selling Blarcamesine..
They are going to have a much different problem..
Managing OFF Approved malady treatment
Scripts.. they going to have to keep track of a lot of different responses for a lot of different diseases maladies well before any trials are run..
They are going to have to figure out..
Using full blood or data in..
What NOT to use Blarcamesine for…
Because the S1r IS the peach of human health
It will not be difficult to sell Anavex’s Blarcamesine.
Just have to answer the phone .
And have a lot of phone lines.
Pharma sales used to be tough before you could buy out the media..
Now you just bribe the media with ad dollars and watch h the phone rings.
Don’t need BP partner for that..
No sir.. they can hold onto
Their cash..
Then watch as the world becomes healthier and happier(stops depression)
All around them..
George why do you bother
Can’t you see a wolf in sheep’s clothing?
Shorty can’t battle MOA topic ..
Not enough info to lie abour
Think the MOA full blood ( big word here I can’t remember ) will allow vigilance with safety to quickly isolate any negative anomalies..
Beeeeuuuuutiful
We are in 2nd half..
What a great position!
Then throw in prophylactic use and safety..
Beeeeiuuutiful
Fun to read again..
How is Michael J Fox not on this
Super Pill?
Anavex presents at AAIC, 2 Aug 2022: “Study of the mechanism of action of Blarcamesine (Anavex 2-73): whole blood transcriptomics analysis identifies treatment impact on compensatory pathways by restoring key neurodegenerative pathways functionality, including Alzheimer’s Disease Pathway”
Is this why?
Wonder if annovis could give us a company update on Clinicals and new drug developments?
Very exciting .. I have been taking. Vinia
solution potent form of Resveratol for a few months.. last two nights took before bed.. awesome dreams..( usually take in morning)love the Vinia ..Bioharvest has too many shares out to move the needle.. yet..but think long term they will do well
Anyway know a lot of people here for hope.. viNIA has helped me
They have to have some data confirming
the prophylactic action
Either through delayed OLE or chemistry..
It’s exciting stuff..
I take DM as a prophylactic..
2weeks on .. months off
Because stock tightly held
and distorters can’t get paid
This is good news..
But the hammer is. A phase 1/2 ? in severe ad..of their new drug..
When will THAT news be out?
Congrats Maria!!!!!
Steady
But IF we do increase actual sigma 1 receptors .. which is a possibility with increased signaling(or is it?)
The human body is magical
Have as-nylons seen anywhere the claim that Blarcamesine INCREASES actual S1r receptors?
Think its big leap to think increased mRNA expression of S1r means increase in S1r ligands.. more likely when S1r agonized increases mRNA expression…
That would be AWESOME beyond humanity IF
We actually INCREASED S1r receptors in the human body..
IF we PROVE THAT…KATY BAR THE DOOOOOOOOOOOR
Well when they become
The Mousavex! They will be able to do
Super mouse things!
Like remember where you put your keys!
Tell you why you just walked out the front door!
Remind you to take a shower!
Tell you why you like this relative!
The Mousavex!
Another 200k after close
Sublime
Tag it
Postie
I see this as an entire industry like diabetes &. Insulin
S1r expression & Blarcamesine
They reported on this..
I think one of the ole was delayed..
Could some sort of fed $$ be coming our way? That would portend the volume we are seeing…someone called Nancy..
Yes the volume at the end of day has been almost 2-300,000 ..so 2 million might seem high … but 500k mor into close.. then another 500k at the close..
I am trying to research how important MOA understanding is to drug acceptance and approval
Clinical and Translational Science
Wiley-Blackwell
Approval success rates of drug candidates based on target, action, modality, application, and their combinations
Shingo Yamaguchi, Masayuki Kaneko, and Mamoru Narukawa
Additional article information
Associated Data
Supplementary Materials
Abstract
The current success rate of a drug candidate, from the beginning of the clinical trial to receiving marketing approval, is about 10%–20%, and it has not changed during the past few decades. Therefore, pharmaceutical companies are under pressure to select one compound, among many others, with a high probability of success. The differences in drug features affect their probabilities of approval success. In this study, we examined the approval success rates of drug candidates, developed in the United States, the European Union, or Japan, by focusing on four parameters (“drug target,” “drug action,” “drug modality,” and “drug application”) and their combinations, and identified factors that conditioned the outcome of the drug development process. We obtained a total success rate of 12.8%, after evaluating 3999 compounds. Moreover, after analyzing the combinations of these parameters, the approval success rates of drugs that corresponded to the following categories—a stimulant in drug action or an enzyme in drug target and biologics (excluding monoclonal antibody) in drug modality—were high (34.1% and 31.3%, respectively). Univariate and multivariate logistic regression analyses revealed that stimulant in drug action, and “B” (blood and blood forming organs), “G” (genito-urinary system and sex), and “J” (anti-infectives for systemic use) in drug application were statistically associated with high approval success rates. We found several parameters and their combinations that affected drug approval success rates. Our results could assist pharmaceutical companies in evaluating the probability of success of their drug candidates and, thus, in efficiently conducting the clinical development process.
Study Highlights
WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC?
Differences in drug features affect their probabilities of successful development.
WHAT QUESTION DID THIS STUDY ADDRESS?
This study examined the approval success rates of drug candidates, developed either in the United States, the European Union, or Japan, based on four parameters (“drug target,” “drug action,” “drug modality,” and “drug application”) and their combinations, to identify factors that could change the outcome of the drug development.
WHAT DOES THIS STUDY ADD TO OUR KNOWLEDGE?
Approval success rates of drugs with a stimulant as drug action or enzyme as drug target and biologics (excluding monoclonal antibody) as drug modality were high. The multivariate logistic regression analysis showed that a stimulant or “B” (blood and blood forming organs), “G” (genito-urinary system and sex), and “J” (anti-infectives for systemic use) as drug application were statistically associated with high approval success rates.
HOW MIGHT THIS CHANGE CLINICAL PHARMACOLOGY OR TRANSLATIONAL SCIENCE?
Our results help pharmaceutical companies to evaluate the approval success of a drug candidate based on the parameters and, thus efficiently advance its clinical development.
INTRODUCTION
The drug research and development process include creating a drug, conducting preclinical and clinical studies, and receiving marketing approval after its regulatory review. This process is associated with an extremely low success rate, ~ 1 in 20,000–30,000. 1 Additionally, the clinical development of a candidate compound, from the start of a clinical trial to marketing approval, has a low success rate (10%–20%) and requires a huge investment that continues increasing year by year, which indicates that the efficiency of this process has been decreasing. 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 The success rates to transition between clinical trial phases are different, as the success rate from phase II to III is lower than those from phase I to II and phase III to commercial approval. 7 , 9 , 10 Moreover, the approval success rate of a licensed drug candidate is higher than that of a self-originated candidate. 6 , 9 , 12 Against this background, pharmaceutical companies are under pressure to select a drug candidate with a high probability of success, among many compounds, and to efficiently conduct the clinical development. Thus, pharmaceutical companies are required to accurately evaluate the probability of success of drug candidates from various points of view.
Drug candidates have various features, and their differences affect the probability that the drug reaches the market. 6 , 7 , 8 , 10 , 12 , 13 , 14 , 15 , 16 , 17 For instance, the approval success rates of drugs that target molecules that are not in the host, such as in bacteria and viruses, were much higher than those that target host molecules in vivo. 13 In oncology, the attrition rate of kinase inhibitors is low compared to that of the average of all oncology drugs, 14 possibly because the target and the mechanism of action (MOA) of kinase inhibitors are better known than those of typical cytotoxic drugs, thus improving the selection of patients in clinical trials by using biomarkers. 14 Regarding drug action, although very few studies have reported the relationship between drug action and success rate, among the drugs targeting G-protein-coupled receptors, the approval success rate of the antagonist was slightly higher than that of the agonist. 15 Multiple previous investigations on drug modality have reported that the approval success rates of biologics are higher than those of small molecules. 6 , 7 , 8 , 9 Regarding the drug application, the approval success rates of oncology and neurology drugs were low; meanwhile, those of drugs for treating infectious diseases, hematology, and ophthalmology were relatively high. 5 , 7 , 8 , 10 , 11 , 16 Because these various parameters influence the approval success rates of the drugs, it is difficult for pharmaceutical companies to estimate the likelihood of the clinical development success. Some companies made a framework based on pharmacological characteristics of drug candidates for improving their success rates, 18 , 19 but they did not include parameters (e.g., drug target and drug action) of a drug candidate itself. Furthermore, although several studies have been conducted so far, the approval success rates and its definition have greatly differed among them, based on data sources and periods of data collection.
Drugs target diverse molecules in the body, and some drugs have different MOAs but target the same molecule. 20 Thus, their approval success rates may vary, depending on the drug target class and MOA. Previous studies, based on a limited number of compounds, compared the approval success rates between different drug target classes 13 and examined the correlation between the clinical development success or failure and the drug target class. 21 However, the relationship between the drug target and MOA and the probability of success in clinical development has not been investigated based on comprehensive candidate compounds. Santos et al. investigated the distribution of drug target classes of approved and discontinued drugs and the relationship among drug targets, drug modalities, and drug applications, but they did not report approval success rates. 22 Although drug modality is limited to the target molecule (e.g., small molecules can target an intracellular molecule whereas antibodies cannot), 23 the approval success rates of drugs after combining parameters, such as target and modality, have not been determined. Thus, how the drug features influence the probability of approval success is still poorly understood.
The present study examined the approval success rates of drug candidates, which were developed in the United States, the European Union, or Japan, by focusing on four parameters (drug target, drug action, drug modality, and drug application) and their combinations, and identified factors that conditioned the outcome of the drug development process.
METHODS
Creation of the database
Drug candidates that started phase I trials in the United States, the European Union, or Japan between January 1, 2000, and December 31, 2010, were identified by searching the commercial Pharmaprojects database (Informa) on July 27, 2019. Because the average time of clinical development (from phase I to approval) was reported to be ~ 96.8 months, 4 we set the date of data cutoff on June 30, 2019. Combination products, biosimilars, vaccines, diagnostic products, and compounds in the preclinical stage were excluded from the study.
The following information regarding the selected drug candidates was also extracted from the Pharmaprojects database: generic drug name, drug name, global status, drug disease, drug disease status, therapeutic class, therapeutic class status, MOA, target, target family, and origin.
First, the selected compounds from the Pharmaprojects database were categorized according to the parameter development status, defined as the development stage of the drug candidate with the most progressed indication (Table S1 shows how the obtained information was related to each parameter). Specifically, the compounds were classified into the following categories: phase I, phase II, phase III, succeeded (including launched, withdrawn, registered, and preregistration), and discontinued (including discontinued, no development reported, and suspended). According to Pharmaprojects, the category withdrawn was provided when the drug approval was withdrawn after reaching the market; therefore, we included withdrawn under the succeeded category. In addition, no development reported was defined as the status in which no records of the compound were reported for 1 year, thus drug development was suspected to be discontinued. Therefore, we included the category no development reported under the discontinued category. Because Pharmaprojects grants the category of suspended to a drug development that was temporarily stopped, this category was included under discontinued. Last, compounds under phases I, II, and III, with unclear results were excluded from this analysis.
Later, the remaining compounds were categorized according to four parameters (target, action, modality, and application), based on the information obtained from Pharmaprojects (Table S1) or by searching for public information (including research papers and company press release). If the information regarding a compound was not obtained from any source, it was labeled as not applicable.
Target Compounds were classified according to their targets into the following categories: receptor, enzyme, ligand, ion channel, transporter, other (proteins related to the cytoskeleton, extracellular matrix, apoptosis, cell cycle, transcription factor, protein degradation, blood clotting, DNA repair, and targeting DNA or RNA), and target unknown (target not identified).
Action (MOA of drug candidate) Compounds were classified into the following categories: inhibitor, agonist, antagonist, stimulant (target-stimulating agents), other (including enhancer, desensitizer, modulator, scavenger, sensitizer, and stabilizer), and action unknown (MOA not identified).
Modality Compounds were classified into the following categories: small molecule, monoclonal antibody (mAb), biologics (excluding mAb), and novel modalities (including nucleic acid, cell therapy, gene therapy, and viral medicine).
Application (therapeutic application of drug candidate) Compounds were classified according to the Anatomical Therapeutic Chemical (ATC) codes, 24 into the following categories: “A” to “V,” multiple ATC codes (which corresponded to compounds with multiple therapeutic applications that have progressed to the same development stage), and application unknown (therapeutic application not identified).
Categories “A” to “V” corresponded to: “A” (alimentary tract and metabolism), “B” (blood and blood forming organs), “C” (cardiovascular system), “D” (dermatologicals), “G” (genito-urinary system and sex), “H” (systemic hormonal preparations, excluding sex hormones and insulins), “J” (anti-infectives for systemic use), “L” (antineoplastic and immunomodulating agents), “M” (musculo-skeletal system), “N” (nervous system), “P” (antiparasitic products, insecticides and repellents), “R” (respiratory system), “S” (sensory organs), and “V” (various).
After assigning to each compound a category for all the parameters, only the drugs with complete category information (target, action, modality, and application) were evaluated in this study.
Calculating the approval success rate
The approval success rate (%) was calculated by dividing the number of succeeded compounds by the total number of compounds (both succeeded and discontinued) and multiplying the result by 100. The approval success rates for the four parameters (target, action, modality, and application) and their combinations (target and action, modality and target, and modality and action) were calculated. Regarding the combination of target and action, only action categories considered to work against each target category were used and the rest were classified as others. Compounds without specific category information (other and target/action unknown) were excluded from the analysis for the combination of parameters.
Statistical analyses
We implemented univariate and multivariate logistic regression analyses using the parameter development status (succeeded and discontinued), as a response variable, and the four parameters (target, action, modality, and application), as explanatory variables, to identify factors associated with the outcome of the clinical development. Statistically significant results corresponded to p < 0.05. The analyses were performed using StatsDirect software, version 3.2.8 (StatsDirect Ltd).
RESULTS
Out of 5681 initial drug candidates that started their clinical development between January 1, 2000, and December 31, 2010, in the United States, the European Union, or Japan, 813 compounds met the exclusion criteria, thus they were removed from the analysis. Next, the parameter development status was applied to the remaining 4868 compounds (Figure 1 and Table S2). After eliminating 673 compounds under development (phases I, II, and III), which contained unclear results, the remaining 4195 compounds were classified according to 4 parameters (target, action, modality, and application; Table S3). Finally, 196 compounds, including at least one not applicable category in any of the parameters, were excluded, resulting in 3999 compounds that were evaluated in the present study (Figure 1). Overall, the numbers of compounds under the succeeded and discontinued categories were 513 and 3486, respectively, and the approval success rate in total was 12.8%.
Figure 1
Figure 1
Database creation. N, number of compounds
The approval success rate associated with each parameter is shown in Figure 2. Regarding the target parameter, the success rates of ligand and target unknown categories were the lowest, 5.4% and 5.5%, respectively (Figure 2a). Regarding success rates related to the action parameter, agonist and stimulant categories had higher rates than those of antagonist and inhibitor (Figure 2b). However, the success rate of the category action unknown was the lowest. When analyzing the modality parameter, the success rate of the biologics (excluding mAb; 15.2%) category was the highest, followed by those of small molecules (13.0%) and mAb (10.7%) categories, and last by that of novel modalities category with lowest rates (Figure 2c). Regarding the application parameter, success rates of “B,” “G,” “J,” and “S” categories were high (Figure 2d). In contrast, the success rates of the categories “L,” “M,” “N,” and “R” were lower than the total approval success rate (12.8%). Moreover, the success rate of the multiple ATC codes category was the lowest.
Figure 2
Figure 2
Comparison of approval success rates for target, action, modality, and application parameters. Success rates of (a) different targets. The category other included compounds targeting proteins related to the cytoskeleton, extracellular matrix, apoptosis, ...
Table 1 shows the approval success rates for the combinations of parameters. Analysis of the combination of target and action parameters revealed that the success rates of the combinations enzyme and stimulant (n = 94, 23.4%) and ion channel and agonist (n = 28, 21.4%) were the highest (Table 1). Among the compounds targeting ligand, antagonist was the only action parameter with success. Among the compounds targeting receptor or ion channel, the approval success rate of agonist were ~ 7% points higher than those of antagonist. For the combination of modality and target parameters, the combination of biologics (excluding mAb) and enzyme (n = 64, 31.3%) resulted in a high approval success rate (Table 1). Among the compounds targeting ligand, mAb (n = 56, 7.1%) and biologics (excluding mAb, n = 15, 6.7%) were the only modality parameters with success. The combination of mAb and receptor was associated with a higher approval success rate of 13.9%, compared to the overall success rate of mAb (10.7%). For the combination of modality and action, combinations of small molecules and agonist (n = 587, 20.1%), and biologics (excluding mAb) and stimulant (n = 88, 34.1%) resulted in high approval success rates (Table 1).
Table 1
Table 1
Approval success rates for combined parameters: target and action, modality and target, and modality and action
Table 2 shows the different parameters associated with the clinical development outcomes. Categories that statistically, significantly affected the approval success rates according to the univariate logistic regression analysis were: ligand and target unknown under target parameter (reference: receptor), agonist, antagonist, stimulant, and action unknown under action parameter (reference: inhibitor), novel modalities under modality parameter (reference: small molecule), and “B,” “G,” “L,” and multiple ATC codes under application parameter (reference: A [Alimentary tract and metabolism]; Table 2). As a result of the multivariate logistic regression analysis, four factors were associated with high approval success rates: stimulant under action, and “B,” “G,” and “J” under application, and three factors were associated with low approval success rates: action unknown under action, novel modalities under modality, and multiple ATC codes under application (Table 2).
Table 2
Table 2
Results of univariate and multivariate logistic regression analyses
DISCUSSION
In the present study, we calculated the approval success rates of drug candidates that started their clinical development between 2000 and 2010 in the United States, the European Union, or Japan, based on four parameters (target, action, modality, and application) and their combinations. As a result, we found several parameters and their combinations that affected drug approval success rates. It should be noted that, in the present study, probability of success by drug action and those by the combinations of the parameters were identified, which have not been fully studied so far.
We used the final outcome of the clinical development for calculating the drug approval success rates, as previously defined by Shih et al. 13 Although they included compounds that were withdrawn under the discontinued category, we included such compounds in the succeeded category because they received approval once. Additionally, many previous studies focused on the success rate of each phase transition (phase I to II, phase II to III, and phase III to approval), 5 , 6 , 7 , 8 , 9 , 10 , 11 , 14 but others used the final results of development. 13 , 22 In addition, the definitions and calculation methods of the success rates were various. In our study, the approval success rates were focused on the final outcome of the clinical development process rather than on the phase transition. Because the approval success rate obtained in the present study (12.8%) was similar to that reported by previous studies, which used data from similar periods as ours, we considered that our calculation of the approval success rate was valid.
Although some studies have investigated how target classes of drug candidates affected the drug discovery effectiveness, 13 , 21 , 22 few have focused on ligands. Santos et al. classified and compared drug targets in their ability to condition the approval of compounds, but they did not include ligands in their classification. 22 In our study, the approval success rate of the ligand was lower than those of other targets (Figure 2a), according to the univariate logistic regression analysis; however, the association was not confirmed in the multivariate analysis (Table 2). Ligands transduce the signal intracellularly by binding to their receptors after being secreted extracellularly, but other target molecules (receptor, ion channel, and transporter) are localized at the plasma membrane. 25 , 26 , 27 , 28 Therefore, we assumed that targeting a ligand is hard to control because the compounds need to catch the molecule extracellularly released, 28 , 29 thus the determination of the proper compound doses is difficult to perform. However, there is a possibility to increase the success rates of ligands by combining genetic insight, because Nelson et al. reported that success rates in clinical development of genetically validated targets were twice higher than those of not validated targets. 30
We confirmed that the approval success rate of stimulant was highest in action, and stimulant was associated with high approval success rate from the result of multivariate analysis (Figure 2b
Good volume in a down market..
See where it goes
Mr N thanks you all for your donations
I was thinking ..
A conference Video before & after of PDD treated
A conference Video of before & after of AD treated
A conference video of before & after of Rett Syndrome
We are doing videos.. let’s do videos
I believe through OLE anavex has found
That Blarcamesine has a lasting impact even AFTER dosage has stopped.
I would see a seasonal prophylactic dosage.. like a two week spring season
MOA announcement is big deal..
Think that driving force right now..
MOA is one of final launch codes required
Appears to remove plaque and slow progression of mental decline..
Wonder how it will work while taking a S1r agonist / M1 agonist which re instates cellular homeostasis?
If you prevent plaque buildup in first place
why would you take this? You would not
Never gets old