Drug development research drives the biopharma industry outlook. A milestone for drug discovery was the establishment of the Precision Medicine initiative by the USFDA, which shaped the industry’s transformation. This regulation not only formalizes the qualification of biomarkers but also encourages clinical trial efficiency by application in the evaluation of patient inclusion/exclusion and determining the biological responses of patients after therapeutic administration. Moreover, the analytical validation and qualification of biomarkers also link their usability in determining the primary and secondary endpoints of clinical trials. Thus, biomarkers are becoming ubiquitous in the discovery, development, and validation of drugs and novel therapies.
A significant change observed recently is the shift from drugs for morbidities affecting millions to orphan drugs (which treat diseases affecting very small patient populations). Meanwhile, greater drug safety and efficacy remain central to the clinical development cycles as the early-to-market competition surges. Makers of biomedical sensors have also hopped into the bandwagon as microarrays and nanosensing technologies assume crucial roles in the clinical application and quantification of biomarkers such as small molecules, electrolytes (Xsensio is a good example), and metabolites. Therefore, here are a few current examples of biomarker applications that exemplify their effectiveness in the clinical development of pharmaceutical and novel therapeutic products.
Current applications of biomarkers
1. The development of therapeutic agents for Alzheimer’s disease
Alzheimer’s disease remains as a non-treatable disease, with various drug development failures to its credit. While the clinical development of drugs to reduce its morbidity and tackle its symptoms is underway, biomarkers enabled an improved understanding of the various manifestations of AD, its different types, its evolving mechanisms, and effectively target tau and amyloid. To that effect, even the USFDA has published guidance on the role of biomarkers in staging the disease including prodromal AD. Moreover, a research framework was established to increase the diagnostic efficiency of AD based on amyloid, tau, and neurodegeneration biomarkers introduced by the National Institute on Aging (NIA) and the Alzheimer’s Association.
As of 2019, in the ongoing clinical development for Alzheimer’s disease, the following biomarkers have been in use: amyloid and tau in cerebrospinal fluid (27 clinical trials), fluorodeoxyglucose-PET (1 trial), volumetric magnetic resonance imaging (10 trials), or amyloid PET (10 trials). Amyloid-PET and CSF amyloid were the most commonly used biomarkers for disease staging and patient inclusion.
2. Predicting Disease Progression in Polycystic Kidney Disease
Urinary diseases present various levels and types of toxicities, especially kidney diseases. To reduce the number of cytotoxicities due to drugs or novel therapies, clinical trial designs embed inclusion criteria based on baseline characteristics and disease-specific biomarkers. Earlier, toxicity cases in clinical trials were as high as 43%, while the number of cases in preclinical studies went up to 71%.
A recent study including 104 patients with autosomal dominant PKD used the following inflammatory, glomerular, and tubular damage markers to segregate patients: albumin, IgG, kidney injury molecule−1 (KIM-1), N-acetyl-β-d-glucosaminidase (NAG), β2 microglobulin (β2MG), heart-type fatty acid-binding protein (HFABP), macrophage migration inhibitory factor (MIF), neutrophil gelatinase-associated lipocalin (NGAL), and monocyte chemotactic protein−1 (MCP-1), measured glomerular filtration rate (mGFR), and height-adjusted total kidney volume (htTKV). These biomarkers were instrumental in diagnosing patients, determining the pharmacogenetic tolerance to pharmaceutical compounds (therapeutic drug monitoring), quantifying the disease progression and identifying the prognostic indicators in each patient for end-stage renal disease (based on the total kidney volume).
On the other hand, genotypic biomarkers have been used to understand the disease progression trends and the risk factors associated with the development of end-stage kidney disease. The qualitative assessment of genotypic and inflammatory biomarkers (such as macrophage migration inhibitory factor and MCP-1) can indicate the tubular damage in polycystic kidney disease and predict the patients’ eligibility for kidney replacements. To that effect, a small, ongoing clinical trial on PKD (PKD Biomarkers Study) focuses on creating a biorepository of urinary biomarkers for PKD. The trial has enrolled not only patients with a history of PKD but also those with a family history of PKD along with healthy controls.
3. Novel Immuno-oncology Biomarkers for Personalizing Cancer Therapy
It’s no more a secret that only 12-14% of new drug applications are met with successful marketization approval from the USFDA. Yet, at least 2,000 therapies are under clinical development only for treating cancers. What’s more, companies have shifted the focus of cancer treatment to personalized or precision medicine, wherein therapies are administered only to a target group of individuals having a specific mutation or immune-oncological characteristic. This has improved the use of immunotherapies and birthed the class of novel immuno-oncology biomarkers. These immune-oncology markers (mutant proteins and antigens) are used in smaller late-stage trials primarily testing killer and helper T-cell immunotherapies. Recently, the use of immune-oncological biomarkers with immune checkpoint inhibitors was expanded to quantify their increased effectiveness and find target-specific candidates for immunotherapies.
Lately, genetic biomarkers of different cancer types were utilized to assess the magnitude of adverse effects following chemotherapy. One study focused particularly on chemotherapy-induced cachexia syndrome and revealed that every patient undergoing chemotherapy has a different tumor-specific protein secretion that correlated with the prevalence of cachexia and average weight loss for each type.
Moderating the doses of chemotherapy and studying the physiochemical responses of patients in concert with their individual genetic profiles is being shown as a promising avenue to reduce cancer-related mortality. Researchers are even expanding this method in prostate cancer to study the changes in the genetic profile of the carcinogenic cells to create safer, targeted therapies. Since cancer or chemotherapy-induced cachexia-anorexia is a complex multifactorial syndrome, a combinatory treatment approach using a small molecule with immunotherapy, based on tumor genetic profiling is under preliminary evaluation in mice models.
4. Identifying Diagnostic & Prognostic Biomarkers for Drug Discovery of Cystic Fibrosis
Cystic fibrosis is a rare inheritable disease affecting the lungs and the pancreas, which remained as a disease with an unmet medical need. With the amendments in the USFDA Orphan Drug Act and its massive adoption into mainstream pharmaceutical R&D in the last few years, the fate of patients with cystic fibrosis changed as their hopes of treatment became a reality. The genetic disease occurring because of mutations in the CFTR gene presents with various genetic, biochemical, and physiological biomarkers.
Several diagnostic and imaging biomarkers have been identified that enable its earlier diagnosis and are used to prevent its life-threatening manifestations with higher success rates. A Biomarker Validation and Qualification study on biomarkers for cystic fibrosis revealed that the specificity of biomarkers has to be evaluated to demonstrate the biological efficacy of new therapies, confirm the mechanism of action, and inform dose selection. The G551D mutation is used as a predictive biomarker to evaluate the efficacy of Ivacaftor clinically, while the 8-week change in FEV1 was remarked as a pharmacologic biomarker that measured the dynamic changes to the body because of Ivacaftor administration.
Sweat-chloride concentration, nasal potential difference, and intestinal current were detected as in vivo biomarkers of cystic fibrosis used for characterization of an individual’s presentation of cystic fibrosis and the genetic function of CFTR gene. In addition, R117H, F508del CFTR, and G551D CFTR gene profiling can elucidate the dose-dependent bioactivity of ivacaftor in patients having these mutations. Similarly, infections by pathogenic bacteria such as methicillin-resistant Staphylococcus aureus, Pseudomonas aeruginosa, and Burkholderia cepacia complex and bacterial density were postulated as biomarkers of infection. Therefore, these biomarkers were used extensively in randomized clinical trials for evaluating the efficacy of combination therapies, such as that of tezacaftor + ivacaftor + elexacaftor.
5. Detecting Cardiovascular Biomarkers to Re-evaluate treatments for CVD
Cardiovascular disease remains the leading cause of mortality rates globally. The situation is complicated by the failure of experimental therapies such as CETP inhibitors—Torcetrapib and Dalcetrapib—which were expected to prevent/slowdown atherogenic activity. CETP, a cholesteryl ester transfer plasma protein, mediates the transfer of cholesteryl ester from high-density lipoprotein (HDL)-cholesterol to proatherogenic very-low-density lipoprotein (VLDL)-and low-density-lipoprotein cholesterol (LDL-C).
Unlike statins, which effectively reduce LDL-C while not affecting residual cardiovascular risk, CETP inhibitors elevate HDL-C but unexpectedly increased cardiovascular morbidity and mortality in previous clinical trials, thereby questioning the cardioprotective effects of high HDL-C. Dalcetrapib was being tested in patients with acute coronary syndrome having a homozygous polymorphism rs1967309 of the ADCY gene. However, unlike evacetrapib, it could not reduce LDL-C. Subsequently, pre-inclusion genetic testing was concluded to be detrimental for greater clinical efficiency following a post-hoc analysis of its placebo-controlled trial, in which the number of major adverse cardiovascular events reduced by 39% in the homozygous population.
Besides these massive clinical failures, the industry spending on R&D is assumed to reduce in the years to come. Moreover, greater regulatory hurdles and data-dependent decision-making will remain as the perennial challenges. Therefore, molecular biomarkers with stronger preclinical data are warranted to improve therapeutic efficiencies and optimize R&D costs.
The emerging technologies of genomics, proteomics, and metabolomics combined with physiological profiling and imaging modalities provide valuable insight. Furthermore, differential gene and protein expression in disease or following drug treatment would be more frequently available. Thus, personalized therapies are expected to dominate the therapeutic landscape in the years to come.
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