Innovations for Improving Contact Lens Designs

Technological devices are playing a role in how industry is advancing the designs of multifocal contact lenses.

By Alexis K.S. Vogt, PhD

Virtually all adults own some type of digital media hardware. Two out of three adults own two or more Internet-connected devices, with multiple ownership peaking at the ages of 30 to 39 years.1 By 2014, 89.5 million Americans are expected to use tablets regularly.2 Adults who are in the 30- to 40-year-old range spend an average of 10.5 hours per day using computers or other technology devices.3 About 67% of adults in this same age group use a smartphone,1 and adults 35 to 55 years old average more than 1,100 text messages per month.4


Worldwide, eye care professionals are seeing a growing number of patients who are in their early to mid-40s and older who would benefit from presbyopic vision correction. These are patients who need simultaneous correction for near, intermediate, and distance vision. One challenge in this patient population is the contact lens dropout rate. Despite a growing population of adults 45 to 64 years old who need vision care and have an increased interest in contact lenses, actual lens wear among this age group is low (Figure).5 As the size of the presbyopic population increases, so too does the need for eye care practitioners to understand advances in lens optics and their patients’ ever-changing vision needs.

The prevalence of handheld devices and computers coupled with an aging population has driven the contact lens industry toward focusing on specialty lenses for presbyopic correction. Studies have shown, however, that using age as the primary metric to determine individuals’ degree of presbyopia does not sufficiently characterize a patient’s true near addition need.6 Kingston et al investigated changes in retinal image quality, measured with high-contrast visual acuity, to futher stratify the degree of presbyopia. Their results show that although age is a good predictor of accommodative amplitude, individual variability of ocular aberrations, depth of focus, and pupil diameter also play a role in the quantification of a patient’s ability to accommodate.

“Studies have shown, however, that using age as the primary metric to determine individuals’ degree of presbyopia does not sufficiently characterize a patient’s true near addition need.”


Coincidentally, technological devices are playing a role in how industry is advancing the designs of multifocal contact lenses. One innovation in the development of presbyopia-correcting lenses is computer modeling. Computer models of individual eyes provide great insight into how best to design a multifocal contact lens that meets the needs of presbyopic patients. To develop computer models of individual eyes, detailed biometry of the patients’ eyes is necessary. A patient’s higher-order aberrations, residual accommodation, and pupillary size are important to understand when designing a multifocal contact lens. Equally important is an understanding of a patient’s visual acuity in a clini- cal setting. While measuring visual acuity in incremental steps from distance to near (also known as through-focus visual acuity), a patient’s subjective image quality can be gathered. With a comprehensive understanding of a patient’s biometry and through-focus visual acuity, an individual computer eye model can be developed for a specific patient’s eye. The model can then be used to provide a predicted logMAR score for any number of lens designs for each individual eye.

Individual computer eye modeling has been validat- ed in multifocal analysis of simulated retinal images.7 In the multifocal analysis, normalized high-contrast high-illumination, normalized low-contrast high-illumination, and normalized low-contrast low-illumination conditions were evaluated clinically and compared with simulated retinal image quality metrics calculated by the individual computer eye models. In a secondary analysis, a computer model eye with varying degrees of defocus, spherical aberration, and decentration created blurred images, which patients ranked from least to most blurred. The ranking results were compared to the image quality metrics predicted by the computer eye model. The results confirm that simulated retinal image quality metrics outputted by individual computer eye models correlate well with visual acuity results recorded in clinical studies. Thus, individual computer eye models can be used to reliably predict retinal image quality.


With advanced computer modeling, a range of patient variability can be taken into account and designed for. Eye models can be used early in the lens design process, prior to clinical trials, to more efficiently test multiple versions of a lens design. While computer models do not eliminate clinical testing, they make the lens design process more efficient and effective.

This type of innovative computer modeling can be used to design multifocal contact lenses with optimized visual performance across a wide variety of pupil sizes, higher-order aberrations, and residual accommodation to help patients see better across the range of critical real-world conditions, such as reading messages on their smartphone or working comfortably at their computer.

Alexis K.S. Vogt, PhD, is an optical physicist at Bausch + Lomb. Dr. Vogt may be reached at

  1. Multi-sponsor Surveys, Inc. The Study of U.S. Digital Media Engagement. October, 2012. Data on file at Bausch + Lomb.
  2. Euromonitor International: USA: Country Pulse. December 2011. Data on file at Bausch + Lomb.
  3. Ipsos OTX and IPSOS Global@dvisor “Socialogue,” U.S. August 21, 2012. Data on file at Bausch + Lomb.
  4. Nielsen, Inc. Number of Messages Sent and Received in the Last 30 Days. The Mobile Media Report: State of the Mobile Media, Q3 2011. Data on file at Bausch + Lomb.
  5. Multi-sponsor Surveys’ 2010 WW Consumer Contact Lens Market Study Interviews conducted in Western Europe, Sweden, Russia, China, India, Hong Kong, Taiwan, Singapore, South Korea, Thailand, Malaysia, Australia and the U.S. Data on file at Bausch + Lomb.
  6. Kingston A, Su-Brady S, Cox I. Presbyopic stratification differences when using an age criterion versus measured thru-focus visual acuity. Poster presented at: The American Academy of Optometry Annual Meeting; October 26, 2012; Phoenix, AZ.
  7. Kingston A, Cox I, Vogt A. Utilizing clinical eye models to predict retinal image quality of individuals. Presented at: The British Contact Lens Association; May 26, 2011; Manchester, UK.