Mind Matters PsychiatryMD

2620 Long Prairie Road  | Suite 100
Flower Mound, TX 75022     

3140 Legacy Drive | Suite 130
Frisco, TX 75034

1701 River Run | Suite 1118
Fort Worth, TX  76107

HOURS: Monday - Tuesday 8-5
Wednesday - Friday 9-6/Lunch 12-1
Saturdays by Appointment
A New Level of Psychiatric Care 

Personalized Medicine
outcomes possible with fewer adverse reactions to treatment. Personalizing treatment represents a substantial shift in medical practice from what worked for a “typical” patient to what now works for each “individual” patient... namely, you.

After all, mental health is a leading cause of disability in the United States and Canada, with approximately one in four adults suffering from a diagnosable mental disorder each year. Of the 27 million Americans currently taking antidepressants, more than half fail to achieve remission, and nearly 40% discontinue treatment within the first 30 days. Additionally, more than 10% of patients taking antidepressants experience significant adverse drug reactions.

The data remains less than optimal for patients prescribed antipsychotic medications, with more than 50% of patients discontinuing antipsychotic medication within their first six months of treatment. A significant portion of antipsychotic treatment discontinuations result from serious drug side effects including rapid weight gain, tardive dyskinesia, diabetes, and sexual dysfunction.

Most of these limiting outcomes are due to the lack of evidence-based genetic information available to clinicians about their patients to guide appropriate medication decisions. Dozens of psychiatric medications exist, each with a different mechanism of action and metabolic profile. Lack of specific patient information forces clinicians to follow standard protocols for prescribing psychiatric medications, despite the fact that there are substantial inter-patient genetic differences in both medication tolerance and response. Psychiatric medication protocols are based on outcome averages from large clinical trials. As a result, clinicians, not knowing how their specific patient will respond, must titrate drug dosages to achieve optimal blood levels. This process, frequently involving multiple drugs, may take months or years, at which point the chances of adverse side effects and insufficient response rates outweigh the prospects of full remission or substantial reduction of symptoms.

The concept of personalized medicine has rapidly gained momentum in the healthcare industry, and at MindMatters, over the past decade. Using both genetic and specific patient non-genetic information, science can narrow down specific population groups that are more or less likely to respond to a medication and experience side effects.

This personalized approach to medicine already has become standard practice in many areas of healthcare including oncological and anticoagulant medication prescribing, where genetic testing is often required prior to prescription. MindMatters is a pioneer in bringing personalized medicine to the field of psychiatry. 

The term pharmacogenomics refers to the study of how genes affect the way a patient responds to medication. Genomic differences can influence the efficacy of medications, can be the source of serious drug side-effects, and can increase the risk of drug-to-drug interactions. By having an evidence-based report of a patient’s genomic drug suitability profile, Dr. Adebogun can better understand how his patients may react to a medication.

Two concepts serve as the backbone of pharmacogenomics. The first is pharmacokinetics, which can be defined generally as the study of how the body metabolizes a drug. Each drug has its own unique metabolic profile, meaning each drug has a specific set of enzymes responsible for catalyzing the absorption, distribution, metabolism, and excretion (ADME) of a medication.

Numerous genomic variants affect how much of these enzymes an individual can produce. Having too little enzyme can cause a drug to build up in a patient’s system and result in adverse drug reactions (ADR’s). Producing too much of an enzyme may cause the patient’s body to excrete a medication too quickly, preventing the drug from ever reaching optimal therapeutic levels. The amount of enzyme available for each individual can be predicted through genomic testing.

The second concept behind pharmacogenomics is pharmacodynamics, which is the process by which a drug affects the body. Pharmacodynamics discerns how and to what degree a drug binds to its intended receptors in the brain. Some of the inter-individual variability in receptor binding can be predicted by genomic variants.

Interpreting numerous pharmacokinetic and pharmacodynamic genomic variants helps Dr. Adebogun better understand how a specific patient may tolerate a medication in advance of making a prescription decision since every patient is a unique individual, and this should be reflected in their medical treatment.

Mind Matters specializes in personalized medicine, the tailoring of medical treatment to the individual characteristics of each patient. Personalized medicine is now possible because sophisticated molecular and informatics tools are available to physicians to individualize patient treatment. New methods to select drugs or treatments tailored to each patient make  better  treatment 
More Information:
To learn more about mental illness and personalized medicine, please refer to the following links:
National Alliance on Mental Health
Personalized Medicine Coalition
Lindner Center of Hope
Mayo Clinic – Personalized Medicine
Cincinnati Children’s Hospital
OSU Center for Personalized Health Care
Pharmacogenetics Knowledge Base [PharmGKB]
1 Kessler R.C, Chiu W.T, Demler O, Walters E.E. (2005). Prevalence, severity, and comorbidity of twelve-month DSM-IV disorders in the National Comorbidity Survey Replication (NCS-R). Arch Gen Psychiatry, 62(6), 617-627.
2 Olfson M. et al. (2006). Continuity of antidepressant treatment for adults with depression in the United States. Am J Psychiatry, 163, 101-108.

3 Marcus S.C, & Olfson M. (2010). National trends in the treatment for depression from 1998 to 2007. Arch Gen Psychiatry, 67(12), 1265-1273.
4 Trivedi M.H. et al. (2006). Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice. Am J Psychiatry, 163, 28-40.
5 Machado M. et al. (2006). Remission, dropouts, and adverse drug reaction rates in major depressive disorder: a meta-analysis of head-to-head trials. Curr Med Res Opin, 22(9), 1825-1837.
6 Lieberman, J.A. et al. (2005). Effectiveness of antipsychotic drugs in patients with chronic schizophrenia. The New England Journal of Medicine, 353(12), 1209-1223.
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